Generating insights based on signals from measuring device

ABSTRACT

A system is described that generates insights on the consumption or usage behavior of a product by analyzing the real-time usage of the product by one or more users. The product is placed on the measuring device for continuous monitoring of the usage of the product by those one or more users in real-time. The measuring device includes a sensor unit that generates weigh data, motion data, location data, and time consumed data of the product and transmits to a computing device. A communication device records the consumption or usage of the product by a user, along with feedback from the user. The computing device generates insights based on the sensed data generated by the measuring device, and recording and feedback at the communication device. The computing device generates reports—one for the user, and one for a merchant of the product and/or similar products—including respective insights.

RELATED APPLICATIONS

This application is a continuation of U.S. application Ser. No.17/858,879 filed on Jul. 6, 2022, which is a continuation of U.S.application Ser. No. 17/535,541 filed on Nov. 24, 2021, now U.S. Pat.No. 11,403,651, which is a continuation of U.S. application Ser. No.17/175,576 filed on Feb. 12, 2021, now U.S. Pat. No. 11,195,189, whichclaims priority to U.S. Provisional Patent Application No. 63/089,956,filed on Oct. 9, 2020. The disclosures of the prior applications areconsidered part of and are incorporated by reference in the disclosureof this application.

TECHNICAL FIELD

The subject matter described herein relates to various implementationsof a device configured to detect consumption or usage of a product, andgeneration of insights based on the detected consumption or usage.

BACKGROUND

Merchants (e.g. manufacturers, distributors, retailers, and/or the like)can benefit from identifying consumption behavior that indicates howusers (e.g. consumers) interact with a product (e.g. how users purchase,perceive, and/or either consume or use the product). For example, amerchant can interpret consumption behavior to understand the needs,desires, habits, patterns, preferences, and problems of users. Based onthe understanding of the needs, desires, habits, patterns, preferences,and problems of the users, the merchant may make several changes andidentifications to maximize sales and customer satisfaction. Suchchanges include modifications to: where the product is placed withinvarious distribution channels, structural details or other features ofthe product, packaging of the product, content of messaging in a digitalcomponent related to the product, mode (e.g., email or text message) oftransmitting the digital component to respective users, timeline forlaunching new products, and/or the like. Such identifications includeidentifications of new opportunities, new segments of target audience,geographies for various business processes (e.g. marketing, sales,manufacturing), and/or the like.

However, the traditional techniques for collecting and understandingconsumption or usage behavior may not be optimal. For instance, whilemerchants have a significant amount of data on the purchase behavior ofconsumers based on retailer data and/or their own sales data, theytypically have little to no idea about the actual consumption or usagedata of those products and/or actual consumption or usage behavior ofconsumers (i.e. users) using those products after the products have beenpurchased by consumers. In some instances, merchants may—eitherthemselves or through other companies-conduct ad-hoc research studies ortap into syndicated research data to try to determine consumptionbehavior. However, such studies and research activities are ineffectivefor many reasons. First, such studies typically provide some indicationof consumption behavior during a particular point in time rather thanover a long period of time that can better indicate consumer behavior.Second, such studies and research activities generate results based ondata of usage informed or claimed by the consumers instead of beingbased on actual consumption, which may not match what the user informsor claims, and thus such results can be inaccurate. Third, some suchstudies may involve a company representative visiting homes or otherlocations of the users to check on usage, but such practices may beunduly burdensome, cost-prohibitive, discouraged by the users, and alsoonly provide infrequent data on what products were finished (fullyused/consumed) but not when, how much, how often, and where they wereconsumed.

Due to such ineffectiveness, such conventional studies and researchactivities do not allow the merchants to obtain deep, authentic, andaccurate insights into consumption or usage data of products and/orconsumer behavior regarding consumption or usage of products by theconsumers or users of those products. For example, the merchants aretraditionally unable to obtain insights (a) based on actual consumptionor use of the product, (b) in an automatic and passive manner, (c) in afast or timely manner, such as in real-time, (d) that are scalable forlarge amounts of users, regions, categories, markets, (e) that areongoing over the life of the product, or a long period of time such asseveral weeks, months, or years, (f) that are presented in a cleareasy-to-comprehend manner. This ineffectiveness of the traditionaltechniques for collecting and understanding consumption behaviorprevents those merchants from providing effectively targetedrecommendations, advertisements, promotions, or messaging to theconsumers or users, and also hinders the ability of the merchants todevelop new products that are effective for those, and/or similar,consumers or users.

SUMMARY

A system is described that cures at least the above-noted deficienciesof the traditional techniques for collecting and understandingconsumption or usage behavior while attaining many advantages. In someimplementations, the system includes a measuring device that can measure(i.e. detect) consumption of a product by a user. The product can be anyproduct that is consumed by a user, such as food products, drugs (e.g.medications), drinks, cleaning supplies, products for hygiene, or anyother product that can be used or consumed by the user. The consumptionof the product, as measured by the measuring device, over a period oftime can indicate consumption behavior of the user with respect to thatproduct. The measuring device can be configured to be coupled-physicallyor communicatively over a communication network—to the product. In someexamples, the measuring device can be in the form of a coaster, a tray,a sleeve (which can be configured to encompass sides of a container suchas a glass or a bottle), a container (e.g. can), an electronic devicesuch as a remote or electronic button, or any other accessory. Theconsumer or user can record, on a communication device, a video showinghow they consume or use the product along with a feedback and/orexplanation provided by the consumer while the consumer or user consumesor uses the product.

The measuring device and the communication device can be connected to abackend server, which can generate insights based on the measuredconsumption. The backend server can generate recommendations based onthe data received from the measuring device and the communicationdevice. Some of the insights and the recommendations can be generatedspecifically for the user, and some of the insights and therecommendations can be generated specifically for the merchant. Theinsights and/or recommendations specific to the user can be provided toa communication device of the user, and the insights and/orrecommendations specific to the entity can be provided to a clientdevice of the merchant. In some examples, the device may also output therecommendations (e.g. display the recommendations on a graphical userinterface, generate audio of recommendations output via a speaker on thedevice, and/or the like). In additional examples, the backend serverand/or the device may send the recommendations to the user via any otherchannel, such as electronic mail, short messaging service (SMS), socialmedia message, or the like.

In one aspect, a method is described that includes one or more of thefollowing. A computing device can receive, from a hub measuring deviceof a plurality of measuring devices that are configured to be coupled toa product and are arranged according to a hub and spoke architecturecomprising the hub measuring device and a plurality of spoke measuringdevices coupled to the hub measuring device, measurement indicatingconsumption or usage of the product by a user. The computing device cangenerate an output comprising a plurality of insights based on themeasurement.

In some implementations, one or more of the following can additionallybe additionally implemented either individually or in any feasiblecombination. The computing device can generate a report comprising atleast some of the plurality of insights, wherein the report can bespecific to one or more merchants of the product. The computing devicecan transmit the report to a client device. In certain implementations,the computing device can generate a report including at least some ofthe plurality of insights, wherein the report can be specific to theuser. The computing device can transmit the report to a communicationdevice of the user.

The receiving of the measurement from the hub measuring device caninclude receiving the measurement from a communication module of the hubmeasuring device. The communication module can receive sensed data froma sensor module of each active measuring device among the plurality ofmeasuring devices. The sensor module can include a motion sensor, aweight sensor, a location sensor, and a time-clock. The sensed data foreach active measuring device can be used to generate the measurement.The generating of the measurement can include removing, from the senseddata, one or more of duplicative data, inconsistent data, a null value,data collected when an error was reported during sensing of the senseddata by the sensor module to obtain the measurement. The sensor modulecan have a form of a capsule configured to be inserted into differentforms of measuring devices.

The computing device can receive, from a smart device, data indicatingan activity indicating a consumption or usage of the activity. Thecomputing device can activate a measuring device of the plurality ofmeasuring devices that is available and geographically nearest to thesmart device to receive additional measurement indicating furtherconsumption or usage of the product by the user. The smart device caninclude an appliance wherein the activity comprises opening or closingof at least a portion of the appliance. The appliance can be one of asmart fridge, smart trashcan, a smart cabinet, a smart sink, or a smartwasher.

The computing device can receive the measurement from the hub measuringdevice of the plurality of measuring devices after the hub measuringdevice has been activated by way of activating an electronic switch. Thecomputing device can receive the measurement from the hub measuringdevice in real-time. In some implementations, the computing device canreceive the measurement from the hub measuring device at programmedintervals of time.

At least one measuring device of the plurality of measuring devices canhave a form of a coaster, a tray, or a container. Each measuring deviceof the plurality of measuring devices can include a hardware modulewithin which electrical circuitry of measuring device resides. Thehardware module can be configured to be placed in any of the coaster,the tray, or the container.

Each measuring device of the plurality of measuring devices can beconfigured to be coupled to the product physically or communicativelyover a communication network.

A measuring device of the plurality of measuring devices can identifythe user. The receiving of the measurement can occur in response to theidentifying of the user.

The computing device can identify content to be output to the user basedon the insights. The output can include digital content to be output onan application of a communication device of the user. The applicationcan be a web browser or a native application installed on thecommunication device.

The computing device can be coupled to the hub measuring device by wayof a first communication network. The hub measuring device can becoupled to the plurality of spoke measuring devices by way of a secondcommunication network that is different from the first communicationnetwork. At least some spoke measuring devices are coupled to otherspoke measuring devices by way of the second communication network.

At least one measuring device of the plurality of measuring devices hasthe form of a coaster. The coaster is configured to be coupled to anapparatus having a movable sleeve to hold the product.

In another aspect, one or more non-transitory computer program productsare described that can store instructions that, when executed by atleast one programmable processor, cause the at least one programmableprocessor to perform operations comprising: receiving, by a computingdevice from a hub measuring device of a plurality of measuring devicesthat are configured to be coupled to a product and are arrangedaccording to a hub and spoke architecture comprising the hub measuringdevice and a plurality of spoke measuring devices coupled to the hubmeasuring device, measurement indicating consumption or usage of theproduct by a user; and generating, by the computing device, an outputcomprising a plurality of insights based on the measurement.

In yet another aspect, a computing device is described that includes atleast one programmable processor, and a machine-readable medium storinginstructions that, when executed by the at least one processor, causethe at least one programmable processor to perform operationscomprising: receiving, from a hub measuring device of a plurality ofmeasuring devices that are configured to be coupled to a product and arearranged according to a hub and spoke architecture comprising the hubmeasuring device and a plurality of spoke measuring devices coupled tothe hub measuring device, measurement indicating consumption or usage ofthe product by a user; and generating an output comprising a pluralityof insights based on the measurement.

Related systems, devices, methods, non-transitory computer programproducts, processors, machine readable media, and articles ofmanufacture are within the scope of this disclosure.

The subject matter described herein provides many advantages. Forexample, the systems and techniques described herein can allow merchantsto obtain deep, authentic, and accurate insights about consumption orusage data of products and/or consumer behavior regarding consumption orusage of one or more products by the consumers or users of those one ormore products. For example, such systems and techniques allow themerchants to obtain insights (a) based on actual consumption or use ofthe product, (b) in an automatic and passive manner, (c) in a fast ortimely manner, such as in real-time, (d) that are scalable for largeamounts of users, regions, categories, markets, (e) that are ongoingover the life of the product, or a long period of time such as severalweeks, months, or years, (f) that are presented in a cleareasy-to-comprehend manner. Effectiveness of the systems and techniquesdescribed herein for collection and understanding of consumptionbehavior enables those merchants to provide accurately targetedrecommendations, advertisements, promotions, or messaging to theconsumers or users, and also allows the merchants to develop newproducts that are effective for those, and/or similar, consumers orusers.

The details of one or more variations of the subject matter describedherein are set forth in the accompanying drawings and the descriptionbelow. Other features and advantages of the subject matter describedherein will be apparent from the description and drawings, and from theclaims.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 illustrates a system view of a system that generates insights onthe behavior of consumption or usage of a product by a user.

FIG. 2 illustrates an exploded view of a measuring device.

FIG. 3 illustrates an exploded view of a communication module of themeasuring device that is communicatively connected to a computingdevice.

FIG. 4 illustrates an exploded view of the measuring device.

FIG. 5 illustrates an exemplary view of the measuring device that iscommunicatively connected to the computing device to trigger anotification on a communication device.

FIG. 6 illustrates an exemplary view of the product connected with themeasuring device.

FIG. 7 illustrates an exemplary view of one or more productscommunicatively connected with one or more measuring devices todetermine the usage behavior of the one or more products by the user.

FIG. 8 illustrates an exemplary view of a graphical user interface ofthe computing device.

FIG. 9 illustrates an exemplary view of a graphical user interface ofthe computing device.

FIG. 10 is a graphical representation of a report that depicts weeklyconsumption of the product.

FIG. 11 is a graphical representation of a report that depicts averageweekly consumption, average weekend consumption, and average weekdayconsumption of the product.

FIG. 12 illustrates an exemplary view of a graphical user interface ofthe client device.

FIG. 13 is a graphical representation of a report that depicts weeklyconsumption details of the one or more products by the user.

FIG. 14 is a graphical representation of a report that depicts weeklyconsumption of the one or more products by the user.

FIG. 15 is an exemplary button device to analyze the product.

FIG. 16 is an exemplary weighing device to determine weigh data of theone or more products.

FIG. 17 is a flow diagram that illustrates a method performed by thesystem that generates insights on the behavior of consumption or usageof the product by the user.

FIGS. 18-23 illustrate different views of an example of a measuringdevice in the form of a coaster.

FIGS. 24-29 illustrate different views of an apparatus that forms thesleeve of a measuring device and that is configured to be attached to acoaster to form the measuring device.

FIGS. 30 and 31 illustrate different views of a measuring device wherethe apparatus of FIGS. 24-29 is attached to a coaster (e.g. coaster ofFIGS. 18-23 ).

FIGS. 32-34 illustrate different views of a tray of a particularmeasuring device that is made operable by coupling (e.g. attaching) thetray with one or more coasters.

FIGS. 35-37 illustrate different views of the measuring device formed bycombining the tray of FIGS. 32-34 with coasters (one example of which isshown in FIGS. 18-23 ).

FIGS. 38 and 39 illustrate different views of a container of aparticular measuring device that is made operable by coupling (e.g.attaching) the container with a coaster (one example of which is shownin FIGS. 18-23 ).

FIGS. 40-42 illustrate different views of the measuring device formed,or being formed, by combining the container of FIGS. 38 and 39 with acoaster (one example of which is shown in FIGS. 18-23 ).

FIGS. 43-45 illustrate different views of an adapter configured tomodify a form factor of the measuring device.

FIG. 46 illustrates a hub and spoke architecture for multiple measuringdevices.

FIG. 47 illustrates an example architecture for a measuring deviceconfigured to act like a spoke within the hub and spoke architecture ofFIG. 46 .

FIG. 48 illustrates an example architecture for a measuring deviceconfigured to act like a hub within the hub and spoke architecture ofFIG. 46

FIG. 49 is a block diagram of an example computer system that can beused to perform operations described above herein.

Like reference symbols in various drawings indicate like elements.

DETAILED DESCRIPTION General Overview

A system is described that can generate insights and recommendationsbased on consumption or usage of one or more products by one or moreusers. The system includes a measuring device to measure characteristics(e.g. weight, motion, location, time of consumption or usage, and/or thelike) of a product, a communication device to provide instructions to auser and receive feedback while the user consumes or uses the product, acomputing device to perform machine learning on data received from themeasuring device and the communication device to generate insights andrecommendations that are respectively specific to user and/or entity(e.g. merchant of the product), and a client device configured to beoperated by the entity. The computing device transmits the insightsand/or recommendations for the user to the communication device, and theinsights and/or recommendations for the entity to the client device.Various architectural modifications are possible, as explained ingreater detail below.

The insights or recommendations for the consumer or user can help theconsumer or user modify consumption or usage habits to improve thequality of life. The insights or recommendations for the entity can helpthe entity assess their product portfolio and campaigns, create newproducts, and make modifications to existing products, content ofproducts, size of products, manufacturing processes, advertisingcampaigns, distribution channels, and/or any other purpose.

Example Architecture of System that Generates Insights andRecommendations

FIG. 1 illustrates a system 100 that generates insights on behavior ofusage or consumption of a product 102 by a user, in accordance with someimplementations described herein. The product 102 may include anytangible good that can be consumed or used. For example, the product 102can include household cleaning items, consumer packaged goods, food andbeverages, and/or the like. The system 100 can include a measuringdevice 104, a communication device 106, a computing device 108, a clientdevice 110 and a communication network 114. The measuring device 104 canmeasure (e.g. sense or detect) consumption or usage of the product 102by the user.

The communication device 106 can be a computing system (e.g. phone,tablet computer, phablet computer, a laptop, or the like) configured tobe operated by the consumer or user of the product 102, can record data(e.g. video, photo or audio) of a consumer or user while consuming orusing the product 102 or other related activities such as opening orstoring the product 102. The computing device 108 can receive data onthe measurements of consumption or usage from the measuring device 104and/or the data of consumption or usage from the communication device106, and can use those data to generate (a) insights based on themeasured consumption or usage of the product 102 and/or (b)recommendations based on the insights. Each of the insights and therecommendations can be generated for (i) an entity that deals with theproduct 102, such as a merchant (e.g. manufacturers, distributors,retailers, and/or the like) of the product 102, or (ii) the user whoconsumes or uses the product. The client device 110 can be a computingsystem (e.g. computer) configured to be operated by a merchant (e.g.manufacturers, distributors, retailers, and/or the like) of the product102. The computing device 108 can transmit the insights and/or therecommendations specific to the user over the communication network 114to the communication device 106, and can transmit the insights and/orthe recommendations specific to the entity over the communicationnetwork 114 to the client device 110.

Measuring Device, Communication Device, and Collection of Data Used ForInsights

The measuring device 104, which measures (e.g. detects or senses) theconsumption or usage of the produce 102, can be coupled to the product102.

Coupling Details for Coupling Measuring Device with Product

The coupling can be physical, or remote over a communication network.The physical coupling can involve the measuring device 104 being eithersimply placed below the product 102 or attached (e.g. affixed by way ofgluing, knitting or threading, welding, twisting and turning multiplecomponents, pressing components with respect to each other or towardeach other, and/or any other one or more attachment mechanisms) to anysuitable area on a packaging (e.g. housing, or any exterior boundary) ofthe product 102. In some instances, the measuring device 104 can haveseparate components such that a first set of one or more components areplaced below the product 102 and a second set (e.g. another differentset) of one or more components is attached (e.g. affixed) to anysuitable area on a packaging of the product 102.

The area, portion or location on the product 102 to which the measuringdevice 104 is coupled can vary depending on the features (e.g.properties or characteristics) of the product, such as the form ofproduct 102 (e.g. solid, liquid, or gas), shape of the product 102,volume of the product, cohesive properties of the product 102, adhesiveproperties of the product 102, surface tension of the product 102,capillary action of the product 102, pressure of the product 102,temperature of the product 102 when the product is to be used and/orstored, viscosity of the product 102, and/or the like. For example, insome implementations, the features may require that the product 102should be as close as possible to the measuring device 104 so that themeasuring device 104 can make accurate measurements, and in such casethe location of coupling on the measuring device 104 may be chosenaccordingly. In other implementations, the features may require that theproduct 102 should be as far as possible to the measuring device 104 sothat the features do not interfere with the measuring functionality orrelated components within the measuring device 104, and in such case thelocation of coupling on the measuring device 104 may be chosenaccordingly.

To physically couple the product 102 and the measuring device 104, themeasuring device 104 can be integrated with, or attached to, a suitablelocation within the product 102 by way of gluing, knitting or threading,welding, magnetic attachment, fastening, taping, any other mechanicalway (e.g. moving, twisting and turning, or pressing two components withrespect to each other so they couple), and/or any other one or moreattachment mechanisms. In cases where the attachment requires combiningof two or more separate components, any of the product 102 and themeasuring device 104 may include some or all of those components, inrespective implementations. For example, the magnetic attachment mayinvolve a metallic strip affixed to the product 102 and one or moremagnets affixed to the measuring device 104; alternately, the metallicstrip may be affixed to the measuring device 104 and one or more magnetsmay be affixed to the measuring device 104. In another example, thefastening attachment mechanism may include a fastener that includes afirst strip (e.g. first fabric strip) with tiny hooks that can mate witha second strip (e.g. second fabric strip) with smaller loops such thatthe hooks temporarily mate with the loops until they are pulled apart;in such case, the first strip can be affixed to the product 102 whilethe second strip can be affixed to the measuring device 104, or thesecond strip can be affixed to the product 102 while the first strip canbe affixed to the measuring device 104. For the attachment mechanism oftaping, different types of tapes can be used for coupling the product102 and the measuring device 104, depending on how strong or long theattachment is desired. For example, materials and/or thickness formingthe tape can vary based on attachment strength and/or length, anddifferent examples of such materials include polypropylene,polyurethane, thermoplastic olefin, low-surface-energy clear coatsystems, rubber (e.g. EPDM rubber), and/or the like.

In some implementations, the product 102 can be communicatively coupledto the measuring device 104 over one or more communication networks, asnoted above. For example, a measuring device 104 can detect motion ofthe product 104, or any component or substance within the product, froma distance (i.e. the detection may be performed remotely, without anyattachment or wired connection between the product and the motionsensor). The motion sensors can be infrared-based motion sensors,optics-based motion sensors, radio-frequency-based motion sensors,sound-based motion sensors, vibration-based motion sensors, and/ormagnetism-based motion sensors. The infrared-based motion sensors caninclude passive sensors and/or active sensors. The optics-based motionsensors can include video and/or camera systems. Theradio-frequency-based motion sensors can include sensors based on radar,microwave and/or tomographic signals. The sound-based motion sensors caninclude microphones and/or acoustic sensors. The vibration-based motionsensors can include triboelectric, seismic, and/or inertia-switchsensors. The magnetism-based motion sensors can include magnetic sensorsand/or magnetometers.

Example Electronics for the Measuring Device

The measuring device 104 includes one or more sensors to measure variousfeatures or characteristics of the product. For example, the one moresensors may include a weight sensor to determine a weight of the product102, a motion sensor to determine a motion of the product 102, and timesensor to determine time-duration of consumption or usage of the product102. Some additional or alternate examples of sensors can be thoseconfigured to detect other features or characteristics including form ofthe product 102 (e.g. solid, liquid, or gas), shape of the product 102,volume of the product 102, cohesive properties of the product 102,adhesive properties of the product 102, surface tension of the product102, capillary action of the product 102, pressure of the product 102,temperature of the product 102 when the product is to be used and/orstored, viscosity of the product 102, and/or the like.

The measuring device 104 further includes a communication module, whichcan include communication circuitry, to enable communication between themeasuring device 104 and other components of the system 100, such as thecommunication device 106 and the computing device 110. The term module,as noted herein, can include software instructions and codes to performa designated task or a function. A module as used herein can be asoftware module or a hardware module. A software module can be a part ofa computer program, which can include multiple independently developedmodules that can be combined or linked via a linking module. A softwaremodule can include one or more software routines. A software routine iscomputer readable code that performs a corresponding procedure orfunction. A hardware module can be a self-contained component with anindependent circuitry that can perform various operations describedherein.

The measuring device 104 can include an electronic switch that canactivate and/or deactivate the measuring of the characteristics (e.g.weight, motion, location, and/or the like) of the product 102 by themeasuring device 104. In some implementations, the activation ordeactivation of the electronic switch can be controlled remotely by thecommunication device 106 and/or the computing device 108. In someimplementations, the electronic switch may be in an activated position,and the manufacturer of the measuring device 104 may position theelectronic switch inside the measuring device 104 such that theelectronic switch cannot be deactivated without expert knowledge ofopening and repairing such measuring devices. In other implementations,the electronic switch may be positioned on an exterior (e.g. housing) ofthe measuring device 104 such that any user may operate the electronicswitch so as to activate or deactivate the electronic switch. Theelectronic switch, when activated, can commence measurement by the oneor more sensors of the measuring device 104. The electronic switch, whendeactivated, can pause or stop measurement by the one or more sensors ofthe measuring device 104.

In some implementations, the measuring device 104 may have minimalelectronic circuitry, such as one or more sensors and a transmitter thattransmit all of the detected data in real-time or at programmed (orprogrammable) intervals of time (e.g. every 5 seconds, every 15 seconds,every 1 minute, every 5 minutes, every 15 minutes, or any other timeinterval) to the computing device 108. Such implementations canadvantageously make the measuring device 104 easy to use, install,and/or repair, as well as less bulky due to less weight because of lesselectronic circuitry within it. In such implementations, the collecteddata is transmitted as is from the measuring device 104 to thecommunication device 106 and/or the computing device 108, which devices106 and 108 may process the collected data.

In some other implementations, the measuring device may have at leastone programmable processor, and a machine-readable medium that can storeinstructions that, when executed by the at least one programmableprocessor, cause the at least one programmable processor to process themeasurements by the one or more sensors before the measurements aretransmitted to the computing device 108. Such implementations may beslightly bulkier due to more electronic circuitry, but such differencecan be minimal. The processing by the measuring device 104 can includeremoval of redundancies from the collected data, and then organizing thedata from which redundancies have been removed so that the organizeddata reduces the time taken by the communication device 106 and/or thecomputing device 108 to retrieve data from the measuring device 104.

In some examples, the processing to remove redundancies can includeremoving, from the collected data, one or more of the following:duplicative data, inconsistent data, null values, data values collectedwhen an error was reporting during the measuring process, and/or anyother erroneous values. In a few examples, the processing to removeredundancies can include normalizing the collected data to organize thedata according to attributes of the collected data, and relationsbetween different collected data. The processing can also includingverifying, before transmission of the collected data, that the data tobe transmitted is complete. Such processing of data can advantageouslyoptimize the bandwidth of transmission because irrelevant or redundantdata is prevented from being transmitted over the communication network114 to the communication device 106 or computing device 108, therebystreamlining the transmission of the data over the communication network114.

In a few implementations, the measuring device 104 may have electroniccomponents, such as one or more controllers, one or more memories, oneor more storage devices, one or more input or output devices, and/or thelike. Further, while the measuring device 104 and communication device106 are shown as separate devices, in some implementations, measuringdevice 104 and communication device 106 may be attached to each other.In a few implementations, the measuring device 104 and communicationdevice 106 may be integrated with each other such that they form asingle structure with a common housing and a shared set of electroniccomponents.

Various sensors are described as being embedded within the measuringdevice 104. In some other implementations, at least some of thosesensors can be embedded within a packaging of the product 102 while theremaining sensors can be embedded within the measuring device 104. Inyet other implementations, the sensors used can be distributed acrossthe packaging of the product 102, the measuring device 104, and thecommunication device 106. The communication device 106 and/or thecomputing device 108 can sync the sensed data between the differentdevices on which sensors are implemented.

Ensuring Accuracy of Collected Data

The one or more sensors on the measuring device 104 make a variety ofdetections or measurements. To ensure accuracy of the measurements, itneeds to be ensured that the measuring device 104 is stable enough tomake measurements. For example, if weight of the product 104 is to bedetected, the measuring device 104 must be placed on a stable surface soas to ensure an accurate measurement of weight.

To ensure stability, the measuring device 104 can compare measurementsat different time points—e.g. a first reading at 12 pm on a particulardata, a second reading at 1 pm on that particular day, and a thirdreading at 2 pm on that particular day. If the comparison results ininconsistent data—e.g. the reading at 12 pm indicates that the product102 weighs 4 kilograms, the reading at 1 pm indicates that the productweighs 3.8 kilograms (indicating that some of the product has beenconsumed), and the reading at 2 pm indicates that the product weighs 4.5kilograms (indicating that the weight of the product 102 increased)while the product has not been refilled—the measuring device 104 canconclude (i.e. determine) that the measuring device 104 is not stable.In such case where instability has been detected, the measuring device104 can (a) discard (or initiate a process to discard) the collecteddata, and/or (b) flag such inconsistency to the communication device 106and/or the computing device 108 to notify the user to place themeasuring device 104 on a stable surface. In implementations where thecollected data is discarded, such discarding of data prevents improperlycollected data from being used to generate insights, thereby rending theinsights to be more accurate and trustworthy.

Similarly, the communication device 106 and/or the computing device 108can also compare the data received at different times or from differentdevices to determine if there is any inconsistency. If the communicationdevice 106 and/or the computing device 108 determine any inconsistency,the communication device 106 and/or the computing device 108 can discard(or initiate a process to discard) the inconsistent data and/or providea notification to the user about the inconsistency (e.g. notificationindicating that the user has mistakenly placed a different product onthe measuring device 104). The process can remove any inconsistencies,including those that possibly may have originated during thetransmission from the measuring device 104 to the communication device106 and/or the computing device 108.

Example Timing of Measurements by the Measuring Device

The measuring device 104 can use an array of sensors to monitor theconsumption or usage of the product 102. In some implementations, themeasuring device 104 can continuously monitor the usage of the product102 in real-time. In certain implementations, the measuring device 104can monitor the usage of the product 102 at programmed (or programmable)intervals of time (e.g. every 1 second, every 5 seconds, every 15seconds, every 30 seconds, every 1 minute, every 5 minutes, every 30minutes, every 1 hour, every day, every 15 days, every 1 month, or anyother time value that can be programmed). In certain implementations,the measuring device 104 can monitor the usage of the product 102 onevery event by identifying actions that indicate a change. Some examplesof such actions include removal of the product 108, or a portion of theproduct 102, to be used, refilling or placing back a product 102 forstorage and/or future use, moving of the product 102, or the like.

The frequency of monitoring can vary based on (a) the storage capacityof the measuring device 104, the communication device 106, and/or thecomputing device 108, and/or (b) the processing capacity of themeasuring device 104, the communication device 106, and/or the computingdevice 108, and/or (c) bandwidth of one or more channels (e.g. one ormore communication channels within the communication network 108) overwhich the measuring device 104, the communication device 106, and/or thecomputing device 108 communicate with each other.

Example Structural Design of Measuring Device

The measuring device 104 can have a structure that matches the design ofthe product 102 to which it is coupled. For instance, where themeasuring device is configured to be placed underneath the product 102,the measuring device 104 can have a cylindrical shape or a box shape(each of which can look like a coaster), which can fit underneath theproduct 102. If the product 102 (or packaging or housing thereof) has aparticular-shaped (e.g. round, square, rectangular, polygonal, or thelike) cross-section at the bottom, the measuring device 104 may have asame or similar cross-section at the top so that the combination of themeasuring device 104 and the product 102 occupy the lease space fordesign efficiency.

In some implementations, the shape of the measuring device 104 can becustomized for each product 102. In other implementations, the shape ofthe measuring device 104 may be based on a set of products. For example,a box-shaped measuring device 104 may be designed to be used for allproducts 102 that are packaged in box-shaped packaging, and acylindrical measuring device 104 may be designed to be used for allproducts 102 that are often packaged in cylindrical packaging (e.g.bottles or jars), so that the mating cross-sections are similar inshape. In cases where a customized design is used for the measuringdevice 104, the customization may be performed to ensure (a) a compactdesign of the measuring device 104 or a combination of the product 102and the measuring device 104, (b) less or optimal usage of physicalspace, (c) improved or optimal performance of electronic componentswithin the measuring device 104, and/or the like.

Another Example Design of Measuring Device Modular Design of SensorCapsule

In some implementations, the measuring device 102 can be in the form ofa physical module (which can also be referred to as a sensor capsule insome implementations, as it includes the sensors) such that the samesensor capsule can be inserted into different items such as a coaster, atray, a sleeve (which can be configured to encompass sides of acontainer such as a glass or a bottle), a container, or any otheraccessory. The sleeve can be made of fabric, foam, plastic, or othermaterials. In some implementations, such items may have some means thatmay allow the sensor capsule to be either inserted into the item orattached to the item.

The sensor module can have a housing that can be made of plastic,rubber, and/or glass. A module as noted herein can include softwareinstructions and codes to perform a designated task or a function. Amodule as used herein can be a software module or a hardware module. Asoftware module can be a part of a computer program, which can includemultiple independently developed modules that can be combined or linkedvia a linking module. A software module can include one or more softwareroutines. A software routine is computer readable code that performs acorresponding procedure or function. A hardware module can be aself-contained component with an independent circuitry that can performvarious operations described herein.

For the sensor capsule to be inserted into such item (e.g. coaster,tray, sleeve, container, or the like), the item may have an opening thatmay be designed to hold the sensor capsule. For example, a coaster mayhave, on top of or beneath its upper surface, a space to hold the sensorcapsule. Similarly, the tray may also have, beneath its upper surface, aspace to hold the sensor capsule. The sleeve may have a space at thebottom of the cylindrical sleeve so that the sensor capsule can beinserted in there. The container (e.g. cup, glass, or jug) may have aphysical space at the bottom that allows the sensor capsule to beinserted in there.

For the sensor capsule to be attached to the item (e.g. coaster, tray,sleeve, container, or the like), the attachment can be performed byattachment mechanism such as gluing, knitting or threading, welding,taping, coupling using one or more of screws or nails, twisting andfitting two or more components until firmly attached (e.g. locked),pressing one component over another until firmly attached to each other(e.g. locked with respect to each other), and/or any other one or moreattachment mechanisms. The attachment can be to any suitable area on theitem. The area, portion or location on the item to which the sensorcapsule is coupled can vary depending on the (a) features (e.g.properties or characteristics) of the product 102 that the item isdesigned for, and (b) the types of sensors within the sensor capsule tobe used. Such features of the product 102 can include form of theproduct 102 (e.g. solid, liquid, or gas), shape of the product 102,volume of the product 102, cohesive properties of the product 102,adhesive properties of the product 102, surface tension of the product102, capillary action of the product 102, pressure of the product 102,temperature of the product 102 when the product is to be used and/orstored, viscosity of the product 102, and/or the like.

For example, in some implementations, the features may require that theproduct 102 should be as close as possible to the sensors so that thesensor capsule can make accurate measurements, and in such case thelocation of coupling on the item may be chosen accordingly. In otherimplementations, the features may require that the product 102 should beas far as possible from the sensors so that features do not interferewith the measuring functionality or related components within the sensorcapsule, and in such case the location of coupling on the item may bechosen accordingly.

In cases where the attachment requires combining of two or more separatecomponents, any of the sensor capsule and the item may include some orall of those components, in respective implementations. For example, themagnetic attachment may involve a metallic strip affixed to the sensorcapsule and one or more magnets affixed to the item; alternately, themetallic strip may be affixed to the item and one or more magnets may beaffixed to the sensor capsule. In another example, the fasteningattachment mechanism may include a fastener that includes a first strip(e.g. first fabric strip) with tiny hooks that can mate with a secondstrip (e.g. second fabric strip) with smaller loops such that the hookstemporarily mate with the loops until they are pulled apart; in suchcase, the first strip can be affixed to the item while the second stripcan be affixed to the sensor capsule, or the second strip can be affixedto the item while the first strip can be affixed to the sensor capsule.For the attachment mechanism of taping, different types of tapes can beused for coupling the sensor capsule and the item, depending on howstrong or long the attachment is desired. For example, materials and/orthickness forming the tape can vary based on attachment strength and/orlength, and different examples of such materials include polypropylene,polyurethane, thermoplastic olefin, low-surface-energy clear coatsystems, rubber (e.g. EPDM rubber), and/or the like.

Material Forming the Measuring Device

The measuring device 104, or a housing (e.g. enclosure) of the measuringdevice 104, can be made of a material that is compatible with thematerial of the product 102 to ensure that the product 102 and/or themeasuring device 104 are not harmed. For example, the measuring device104 (or a housing of the measuring device 104) can be made of a materialthat can remain stable and fully operational at a temperature of storageor operation of the product 102. In some examples, the measuring device104 (or a housing of the measuring device 104) may be configured toremain stable and fully operational in a wide temperature range, whichin some examples can range from −40° C. to 150° C., in certain examplescan range from 0° C. to 100° C., in few examples can range from 0° C. to50° C. Some examples of such materials include fiberglass (which alsoadvantageously does not absorb liquids such as water that may be presentin the product 102), mineral wool (which also advantageously does notmelt or support combustion, thereby making it safe to use for a varietyof types of product 102), cellulose (which is also eco-friendly as ithas a high amount of recycled content), polyurethane foam (which alsoadvantageously is a sound insulator, which can be beneficial for usewith loud products), and/or the like.

The measuring device 104 can have protection mechanisms to avoid beingharmed from spill or leakage of the product. For example, in someimplementations, the measuring device 104 can have a liquid proof orliquid resistance (e.g. water proof or water resistant) housing, whichcan be advantageous where the product is a liquid as the measuringdevice 104 may not be damaged by spill or leakage of the product 102onto the measuring device 104. The liquid proof or liquid resistanthousing can be made with liquid proof or liquid resistance materials,such as polyurethane laminate (PUL), thermoplastic polyurethane (TPU),waxed cotton, nylon, polyester, PVC-coated polyester, laminated fabric,enameled cloth, polyester fleece, microfiber, wool, vinyl, pleather, andplastic.

The measuring device 104 can additionally or alternately be made ofmaterials that have a low coefficient of friction and are abrasionresistance, such as polytetrafluoroethylene (PTFE). Such materials canprevent or reduce friction and abrasions, and thus advantageouslyelongate the life of the measuring device 104.

In some implementations, the material forming the measuring device 104may have a high strength, and some examples of such materials includedense materials such as wood or polymers, and tough materials such assteel. In a few examples, the material forming the measuring device 104may have a high electrical resistivity, and examples of such materialsinclude thermal insulators such as polymers and ceramics. In certainexamples, the material forming the measuring device 104 may be flexibleor elastic, and some examples of such materials include rubber,thermosets, or rubber. In other examples, the material may be stiff, andsome examples of such materials include steel, aluminum alloy orcarbon-fiber. In some examples, the material forming the measuringdevice 104 may be have a low cost of recycling, and some examples ofsuch materials include metals, as they can be easily sorted, remeltedand shaped. In a few examples, the material forming the measuring device104 may have a low energy cost—which can be based on (a) energy requiredto collect/mine the material, and/or (b) energy required to refine,extract or synthesize the material—and an example of such material isaluminum.

Different implementations can use respective sets of one or morematerials, which can be arranged in a manner that allows compactness andusage efficiency of the measuring device 104.

Activation of Measuring Device

The measuring device 104 can include an electronic switch that canactivate and/or deactivate the measuring of the characteristics (e.g.weight, motion, location, and/or the like) of the product 102 by themeasuring device 104, as noted above. The location of the electronicswitch within the measuring device 104 can be varied to provide the easewith which the measuring can be activated or deactivated. For example,in some implementations, the electronic switch may be on the exterior(e.g. housing or enclosure) of the measuring device 104 such that theuser of the product 102 can activate or deactivate the measuring. Inother implementations, the electronic switch may be only in the interiorof (e.g. electrical circuitry within) the measuring device 104 such thatthe user of the product 102 is discouraged from (or, in someimplementations, prevented from) activating or deactivating themeasuring device 104. In implementations where electronic switch is inthe interior of the measuring device 104, the measuring device 104 maybe configured to be activated or deactivated remotely by thecommunication device 106 and/or the computing device 108.

In some implementations, one or more controllers or processors withinthe measuring device may activate the measuring process (i.e. activatethe sensors within the measuring device) in response to an event. Suchevent can vary in different examples.

For instance, in some examples, the event can be receipt of a scan by auser of a machine-readable data representation (e.g. barcode, matrixcode, QR code, and/or the like).

In certain examples, the event can be formation or activation of acommunication channel connecting the measuring device 104.

In other examples, the event can be receipt of a signal from anotherelectronic component (which may or may not be shown in FIG. 1 ) in thesystem 100 that indicates that the product 102 has been, is being, or isabout to be consumed or used. For instance, a controller of themeasuring device 104 can activate the sensors within the measuringdevice 104 in response to a sensor (e.g. motion sensor) within other oneor more devices (e.g. one or more of fridges, trashcans, cabinets,sinks, washing machines, dishwashers, any other one or more places ordevices where the product 102 can be placed, and/or any combinationthereof)—which is communicatively coupled to the measuring device 104over a communication network, such as the communication network114—indicating that the product 102 has been, is being, or is about tobe consumed or used.

For instance, a motion sensor within a fridge may indicate opening of adoor of the fridge, which may indicate that a substance of the product102 is about to be taken out and poured into a container of the product102. Similarly, a motion sensor within a trashcan may indicate openingof a lid of the trashcan, which may indicate that the product 102 or asubstance of the product 102 is being thrown and would not be reused. Ina similar manner, motion sensors within a washing machine or washer mayindicate opening of a lid, which may indicate that the product 102 (e.g.dishwashing detergent or washing liquid) is being used. Similarly, amotion sensor within a cabinet may indicate opening of a cabinet door,which may indicate that the product 102 stored in the cabinet is beingused.

In cases where the communication network 114 is the internet, thecomponents of the system 100, including such other components—e.g. smartfridge, smart trashcan, smart cabinets, smart sink or the like (notshown)—can form an internet of things, which can also be referred to asinternet of products.

In a few examples, the event can be confirmation of an identity of auser that is about to consume the product. The identity of the productcan be created by way of the user inputting authentication data, radiofrequency identification, biometrics-based identification (which mayimplement facial recognition, fingerprint scanning, voiceidentification, eye scanning, and/or the like), identification by way ofmagnetic stripes being used by the user, optical character recognitionof data input by the user, use of one or more smart cards by the user,voice recognition, and/or the like. The user may be required to provideinput to facilitate the identification on the measuring device 104. Insome implementations, the user may be required to provide input tofacilitate the identification on the communication device 106 (e.g. onan application—which can be a browser or a native application-on thecommunication device 106). The identification process to map the user tothe received input data may be performed on the measuring device 104,the communication device 106, and/or the computing device 108 in variousimplementations.

Associating Consumption or Usage of Product with Corresponding User, andCollecting Additional User Data To Allow For Generation Of MoreInformative Insights

Associating the consumption or use of the product with a particular usercan be beneficial in cases where multiple users (e.g. different membersof a family) use a same product, as such implementation allows trackingconsumption or usage of the product 102 by different consumers or users.This can allow generation of insights specific to each user (instead ofthe entire family that may be using the same product). In otherexamples, the techniques may be modified to allow generation of a commonset of insights for all users as a whole (e.g. all the family members)that use a particular product.

The identity of the product can be created by way of the user inputtingauthentication data, radio frequency identification, biometrics-basedidentification (which may implement iris and/or facial recognitionsystem), identification by way of magnetic stripes being used by theuser, optical character recognition of data input by the user, use ofone or more smart cards by the user, voice recognition, and/or the like.The user may be required to provide input to facilitate theidentification on the measuring device 104. In some implementations, theuser may be required to provide input to facilitate the identificationon the communication device 106 (e.g. on an application-which can be abrowser or a native application—on the communication device 106). Theidentification process to map the user to the received input data may beperformed on the measuring device 104, the communication device 106,and/or the computing device 108 in various implementations. In someimplementations, the identification of the user can be performeddetecting proximity between the measuring device 104 and a wearabledevice worn by the user (e.g. bracelet, necklace, anklet, ring, watch,or the like, each of which is configured to communicate with themeasuring device 104 over a communication network) when a usage eventassociated with the product 104 (e.g. weight change and/or motion, asdetected by the measuring device 104) occurs.

In some implementations, the authentication of a user so as to confirmthe identity of a user may include a combination of one or moretechniques, such as a multi-factor authentication. In certain examples,the authentication can include a certificate based authentication,biometric authentication (e.g. facial recognition, fingerprint scanning,voice identification, eye scanning), token based authentication, and/orthe like.

Authorization of Activation of Measuring Device

The communication device 106 and/or the computing device 108 may need toauthorize the initialization of the measuring device 104. For example, auser may be required to use the communication device 106 to upload dataindicating a coupling between the product 102 and the measuring device104 (e.g. physical proximity between the product 102 and the measuringdevice 104, or placement, installation or attachment of the measuringdevice 104 on the product 102) before the measuring device 104 isactivated or initialized. The data indicating the coupling can be in theform of a photograph, video, or textual data. The video or textual datacan include feedback provided by the user, where such feedback canindicate or confirm the coupling.

The computing device 108 can use natural language processing techniquesto analyze the textual feedback to determine that coupling has takenplace, and/or use image processing techniques to analyze the photographsor videos to determine that coupling has taken place. In someimplementations, the computing device 108 may implement a machinelearning model to perform such natural language processing and/or imageprocessing. In a few implementations, the coupling information can beextracted using various algorithms, such as latent semantic analysis,probabilistic latent semantic analysis, latent dirichlet allocation,correlated topic model, any other one or more identification algorithms,and/or any combination thereof.

The machine learning models used to perform such identification may havebeen trained on historical coupling data—i.e. data indicating orassociated with coupling between (a) the measuring device 104 or similardevices and (b) the communication device 106 or similar devices and/orthe computing device 108 or similar devices. The machine learning modelmay have been trained previously by and/or on the computing device 108and/or any other one or more devices, which may be coupled to thecomputing device 108 through a communication network and provide themachine learning model to the computing device 108. In someimplementations, the computing device 108 may implement a software as aservice (SaaS) that performs the training and deployment of machinelearning models, where such training, deployment, and/or storage ofmachine learning models can be performed in a cloud computing systemthat is coupled to the computing device 108.

The machine learning model that is trained and deployed to identifycoupling be can be a supervised model (e.g. a model that involveslearning a function that maps an input to an output based on exampleinput-output pairs) or an unsupervised model (e.g. a model used to drawinferences and find patterns from input data without references tolabeled outcomes). The supervised model can be a regression model (e.g.model where output is continuous) or a classification model (e.g. modelwhere the output is discrete).

The image processing techniques can be performed by the machine learningmodel, or by the computing device 108 without using a machine learningmodel. The image processing techniques to determine coupling can be usedto determine that a user physically placed the measuring device 108adjacent to the product 102 at an appropriate location (e.g. placed ameasuring device in the form of a coaster underneath the product 102).The image processing techniques that determine that the user physicallyplaced the measuring device 108 adjacent to the product 102 at anappropriate location can involve image classification, objectrecognition, object tracking, semantic segmentation, instancesegmentation, pattern recognition, and/or the like.

In response to determination of the coupling, the computing device 108can transmit a signal to the measuring device 104 that can activate orinitialize the measuring device 104. Ensuring a coupling before theactivation or initialization of the measuring device 104 can ensure thatthe measuring device 104 operates only when needed so as to save—and, inturn, optimize or improve the functionality of—computing resources,including processing, storage, and transmission capabilities.

Generation of Notifications and Activation of Sensors in Response toUser Confirmation

A controller of the measuring device 104 can activate the sensors withinthe measuring device 104 in response to a sensor (e.g. motion sensor)within other one or more devices (e.g. one or more of fridges,trashcans, cabinets, sinks, washing machines, dishwashers, any other oneor more places or devices where the product 102 can be placed, and/orany combination thereof)—which is communicatively coupled to themeasuring device 104 over a communication network, such as thecommunication network 114—an activity (e.g. opening of a fridge door,lid, cabinet door, or the like) that indicates that the product 102 hasbeen, is being, or is about to be consumed or used.

In some implementations, the controller of the measuring device 104 maynot activate the sensors within the measuring device 104 in response todetection of such activity at the other device (e.g. fridge, trashcan,cabinet, sink, washing machine, dishwasher, or the like). Instead, thecontroller may (a) generate a notification of the activity to the user,(b) transmit a request for confirmation that the user performed suchactivity, and (c) activate the sensors within the measuring device 104in response to confirmation by the user. Activation of sensors inresponse to confirmation by a user can ensure that data specific to theparticular user is recorded by the measuring device, and preventsrecording of data that should not be associated with or mapped to theuser. This can, in turn, reduce the storage requirements within themeasuring device 104 or any other component within the system 100 thatstores the measured data, and reduce the bandwidth required fortransmitting the measured data.

Collection of User Attributes and Other Attributes

To generate more informative insights, in some implementations, thecommunication device 106 may collect (for purposes of transmission tothe computing device 108) various other details (e.g. user attributesand/or attributes of the product 102, measuring device 104, and/orcommunication device 106) at some point, which can be collected on anapplication of the communication device 106 before the user starts usingthe measuring device 104 to capture the consumption or usage of theproduct 102 by the user.

The user attributes that are collected by the communication device 106can include name of the user, date of birth of the user, ethnicity ofthe user, product preferences of the user, brand preferences of theuser, shopping habits of the user, consumption or usage habits of theuser, and/or residential address of the user. In a few implementations,the user attributes can further include details of a household of theuser, such as the number of people that live in the household, anapproximate size of a house in square feet, household income, number ofpets in the household, types of pets in the household, and/or describingof current living situation.

Other attributes that are collected by the communication device 106 caninclude details of the product 102, details of the measuring device 104,details of the communication device 106, and/or the like. The one ormore details of the product 102 may include data representation on theproduct 102 that is readable by a machine (e.g. barcode of the product102, QR code of the product, or the like), the name of the product 102,a merchant (e.g. manufacturers, distributors, retailers, and/or thelike) of the product 102, a photograph or video of the product 102, aweight reading of the product 102, and/or the like. In someimplementations, the measuring device 104 includes an inbuilt barcodescanner to scan the barcode of the product 102.

In some implementations, the communication device 106 may retrieve suchattributes automatically from an application (e.g. browser or a nativeapplication) of the communication device 106. In a few implementations,the communication device 106 may retrieve such attributes automaticallyfrom an operating system of the communication device 106. Thecommunication device 106 may retrieve these details in an automaticmanner after receiving consent from the user of the communication deviceso as to advantageously respect and protect privacy of the user. In someimplementations, the communication device 106 may retrieve suchattributes in the form of an input provided or initiated by the user.

The communication device 106 may transmit these attributes to thecomputing device 108, which may use these attributes as well to performmachine learning for generating insights.

Provision of Data File to Communication Device and Receipt of Feedbackfrom User While Consumption or Usage of Product

The computing device 108 can transmit a message requesting the user toactivate a camera device prior to consuming or using the product 102.Such message requesting activation of the camera device can betransmitted to an application (e.g. browser or native application) ofthe communication device 106 and/or the measuring device 104. Theapplication can output (e.g. display or generate an audio signalindicating) the message for the user.

The camera device can be either inbuilt within the communication device106, or external to, and communicatively coupled to, the communicationdevice 106. In implementations where the camera device is external tothe communication device 106, the camera device can be physicallycoupled to the communication device 106 or remotely coupled over acommunication network. In this case where the camera device is external,the camera device may be in the form of a wearable device, which a usercan wear.

For example, the camera device may in the form of a neckband or anecklace, which the consumer or user can wear around a neck of the user.The neckband or necklace may be worn around a part of the circumferenceof the neck or the entire circumference of neck. For example, in someinstances, the neckband or necklace may be in the shape of an arc (whichcan be semi-circular, part of a circle, part of an ellipse, or the like)that can be placed around a portion of the neck. In other instances, theneckband or necklace may have a closed shape (e.g. circle, ellipse, orthe like) that can close while the user wears the neckband or necklacearound a neck and can open (e.g. by disengaging two ends) when the userwishes to remove the neckband or necklace around the neck.

While a neckband of necklace is described, in other implementations, thecamera device can be in the form of a brace configured to be placedaround a wrist of the user. In another implementation, the camera devicecan be in the form of a belt configured to be placed around a waist ofthe user. In a few implementations, the camera device can be in the formof an anklet configured to be placed around an ankle of the user. Othervariations of the camera device are possible for other body parts of theuser.

The camera device may include a flash to be automatically used based onthe lighting at the place of capture. In some implementations, the flashcan be manually activated or deactivated.

The camera device can record the consumption or usage of the product 106by way of audio recording and/or video recording. The audio or videorecording can be made in real-time (i.e. as the consumer or userconsumes or uses the product 102 in response to the instructions). Inother words, the audio and/or video recording can be a record showing orindicating the consumer or user consuming or using the product.

During the recording of the audio and/or video recording, the computingdevice 108 can transmit a data file (which can include audio, video,and/or textual components) that can include one or more instructions forthe user. The one or more instructions can include one or moreinstructions to place the measuring device 104 at a particular locationon or adjacent to the product 102, one or more instructions to hold theproduct 102 in a particular manner, one or more instructions to consumeor use the product 102 in a specified manner, and/or the like. The audioand/or video recording can include those instructions as well as user'sresponse to those instructions. The response of the user to theinstructions can be specific actions, such as placing the measuringdevice 104 at a particular location on or adjacent to the product 102,holding the product 102 in a particular manner, consuming or using theproduct 102 in a specified manner, and/or the like. In someimplementations, the data file can include questions (which can be inaudio, video, and/or textual form), and the camera device can allow theuser to provide responses within the data file.

The communication device 106, which includes the camera device, cantransmit the audio or video recording along with the data file, whichcan include responses provided by the user in response to the questions,to the computing device 108. The computing device 108 can use the audioor video recording along with the data file for machine learning togenerate insights.

The stability and quality of the data file (which includes audio, video,and/or text) as transmitted from the computing device 108 to themeasuring device 104 and/or the communication device 106 can beimproved. Similarly, the stability and quality of the data file (whichincludes responses provided by the consumer or user) as well as theaudio and video recording as transmitted from the measuring device 104and/or the communication device 106 to the computing device 108 can beimproved. These improvements can be performed by at least one controllerof the computing device 108, the communication device 106, and/or themeasuring device 104 in various implementations. Such controller canattain improvements as follows.

The controller can separate data packets within data to be transmitted.The data to be transmitted is either the data file that is transmittedfrom the computing device 108 to the measuring device 104 and/or thecommunication device 106, or the data file (which includes responsesprovided by the consumer or user) as well as the audio and videorecording that are transmitted from the measuring device 104 and/or thecommunication device 106 to the computing device 108. The controller canassign the data packets to multiple channels associated thecommunication network 114. The separated data packets can be assigned tothe plurality of channels based on a continuous assessment of latency ofdata transmission within one or more of the plurality of channels. Thecontroller can transmit, over those multiple channels, the data packetswith metadata indicating information regarding sequence of each packetwithin the video. The controller can combine the transmitted datapackets from different channels of those multiple channels based on themetadata.

Generation of Reminders for User to Use Product

In some implementations, the computing device 108 may allow theapplication within the communication device 106 to be programmed by auser to obtain reminders to consumer or use the product at programmed(or programmable) intervals, such as 1 hour, 2 hours, 6 hours, 12 hours,1 day, 5 days, 10 days, 15 days, 1 month, or any other time interval.This feature can be beneficial in consumption of specific products,consumption of which is critical, such as medications, any otherproducts (including food products) that may have been recommended by aclinician, perishable products such as fruits and vegetables, and/or thelike. In such cases, the computing device 108 and/or the communicationdevice 110 can cause the generation of a reminder or an alarm throughthe application installed on the communication device 110.

Categorization of Products on Application on Communication Device

The application on the communication device 106 can receive data thatcan be used by the machine learning model to generate insights. Somesuch data can include various actions performed by the user on theapplication, timestamps for performing such actions, and/or the like. Insome examples, the actions can include: specification of categories ofproducts used by the user in the past programmed (or programmable)periods of time (e.g. products used in the past 1 month, past 6 months,past 1 year, past 2 years, and/or any other time period), receipt orpurchase of products used by the user in such past programmed (orprogrammable) periods of time determined by user input surveys orphysical and/or digital receipt scans, specification of categories ofproducts purchased but not yet used by the user, purchases of suchproducts, barcode scans of products in a location (e.g. home or office)of the user, specification for time-preferences for consumption or usageof each product (e.g. breakfast, lunch, dinner, or the like). In someimplementations, the categories may be preprogrammed for all users, butin other implementations one or more users may be authorized to modify,add, or delete at least some of the categories. Such categorization ofproducts may also be referred to as tagging of the products. In certainimplementations, such categorization or tagging of products may also beused to determine which specific products a user has been requested orinstructed to place on the measuring device 104.

Internet of Things—Interaction with Other Smart Devices to CollectAdditional Event Data to be Used in Machine Learning

The measuring device 102, communication device 106 and/or the computingdevice 108 may be connected to, and retrieve data from, other one ormore devices (e.g. one or more of fridges, trashcans, cabinets, sink,washer, any other one or more places or devices where the product 102can be placed, and/or any combination thereof) that may have sensingcapabilities (e.g. by way of one or more sensors within those otherdevices). Such data can indicate an activity (e.g. opening of a fridgedoor, lid, cabinet door, or the like) that indicates that the product102 has been, is being, or is about to be consumed or used. Suchconnections can be over a communication network. In cases where thecommunication network 114 is the internet, the components of the system100, including such other devices—e.g. smart fridge, smart trashcan,smart cabinets, smart sink or the like (not shown)—can form an internetof things, which can also be referred to as internet of products.

A controller of the measuring device 104 can activate the sensors withinthe measuring device 104 in response to a sensor (e.g. motion sensor)within other one or more devices (e.g. one or more of fridges,trashcans, cabinets, sinks, washing machines, dishwashers, any other oneor more places or devices where the product 102 can be placed, and/orany combination thereof)—which is communicatively coupled to themeasuring device 104 over a communication network, such as thecommunication network 114—an activity (e.g. opening of a fridge door,lid, cabinet door, or the like) that indicates that the product 102 hasbeen, is being, or is about to be consumed or used.

The measuring device 102 and/or communication device 106 may transmitthis data collected from these other devices (e.g. one or more offridges, trashcans, cabinets, sink, any other one or more places ordevices where the product 102 can be placed, and/or any combinationthereof) to the computing device 108, which may such data as well toperform machine learning for generating insights.

In some implementations, the computing device 108 may detect theactivity (e.g. opening or closing of a fridge door, lid, cabinet door,or the like) without using the one or more sensors that may or may notbe present on those other devices (e.g. fridge, trashcan, cabinet, sink,washer, or the like). In such cases, the computing device 108 cantransmit, to the communication device 106, a message requesting the userto activate a camera device to record such activity. The camera devicecan record such activity, such as the opening or closing of a fridgedoor, lid, cabinet door, or the like. The computing device 108 canretrieve the recording, and implement one or more machine learningmodels to determine the occurrence of the activity. The computing device108 can then, upon detection of the occurrence of the activity, transmitinstructions to the measuring device 104 or the communication device 106to activate or deactivate the sensors within the measuring device. Theseimplementations can be advantageous in cases where it is difficult toplace sensors within one or more of those other devices (e.g. fridge,trashcan, cabinet, sink, washer, or the like) to detect the activity(e.g. opening of a fridge door, lid, cabinet door, or the like).

Additional Features of Smart Devices

Some of the smart devices that can be a part of the system 100 include afridge, trashcan, cabinet, sink, washer, dishwasher, and/or the like.Such devices may be referred to as a smart device because of theincorporation of electronic circuitry within them, which can includesensors, as described above.

In some implementations, the smart devices can also include cameraswithin them. Such camera can be used to read machine-readable datarepresentation (e.g. barcode, matrix code, QR code, and/or the like) ofa product placed within that smart device so as to identify the product,and determine (based on the type of smart device) whether the product isbeing stored, used, or discarded. For example, a product 102 placed inthe trashcan indicates that the product is being discarded, a product102 placed in the washer indicates that the product is being used, aproduct 102 placed in the cabinet indicates that the product is beingstored.

The smart devices can further include weight sensors, time sensors,location sensors, energy or power meters, and any other sensor (whichare separate from, but similar to, the sensors within the measuringdevice 104). The weight sensors can indicate the weight of the product102 at different times, which can further indicate the consumption orusage of the product 102. The time sensors can determine the time forwhich the consumption or usage has been determined. The location sensorscan include a global positioning system (GPS) device that indicate anaddress location of the smart device, and an internal location sensorthat can indicate an internal location within the smart device (e.g.second tray from top within the smart fridge), and/or the like.

In some implementations, the motion of an object—which has already beenlocated—may be used to infer the modifications in the location of thatobject. The motion of the object can be measured by a motion sensor,which can be one or more of infrared-based motion sensors, optics-basedmotion sensors, radio-frequency-based motion sensors, sound-based motionsensors, vibration-based motion sensors, and/or magnetism-based motionsensors. The infrared-based motion sensors can include passive sensorsand/or active sensors. The optics-based motion sensors can include videoand/or camera systems. The radio-frequency-based motion sensors caninclude sensors based on radar, microwave and/or tomographic signals.The sound-based motion sensors can include microphones and/or acousticsensors. The vibration-based motion sensors can include triboelectric,seismic, and/or inertia-switch sensors. The magnetism-based motionsensors can include magnetic sensors and/or magnetometers.

The computing device 108 can receive timestamped data, including outputsof each of these sensors, from the smart devices either directly or viathe communication device 106. Such data can be input to the machinelearning model for a more accurate and/or detailed generation ofinsights.

Installation of the Smart Device

While the smart device is installed, the application (e.g. browser ornative application) of the communication device 106 may provideinstructions to the user for installation of the smart device. Theapplication may require the user to input some information to completethe installation process. The computing device 108 can provide suchinformation as input to the machine learning model that is used togenerate insights. Such data can include details of a user (which caninclude details that can uniquely identify the user), specific featuresof the smart device that have been programmed by the user, preferencesof the user for using the smart device, desired operations of the smartdevice, and/or the like.

Syncing of Product Consumption or Usage

To ensure that each component within the system 100 has the most recentdata on consumption or usage of the product 102, the components withinthe system 100—including the measuring device 104, communication device106, computing device 108, and the smart devices—can sync with eachother. The term sync can also be referred to as synchronization,docking, cradling, and/or the like. In some implementations, the syncingmay occur at programmed (or programmable) intervals of time, such as 30seconds, 1 minute, 5 minutes, 30 minutes, 1 hour, 6 hours, 12 hours, 1day, 2 days, 5 days, or the like. The lower the time interval, the moreaccurate will the insights be. Also, this implementation where syncingoccurs at specific intervals conserves computing resources as comparedto an implementation where syncing occurs in real-time. In certainimplementations, the syncing may occur in real-time, and thisimplementation can advantageously result in generation of more accurateinsights.

To sync all of these devices in the system 100, the computing device 108can update a software with data received from any of these devices, andrender that updated data in software to each of the devices so that eachdevice has the most recent data at the time of syncing. The computingdevice 108 can communicate with each other by way of communicationnetwork 114, and/or any other one or more communication networks. Somesuch communication networks can include Bluetooth communication,Bluetooth Low energy, Wi-Fi, cellular networks, or any othercommunication network. In some implementations, the communicationnetwork connecting two or more smart devices described herein can be alow-power, low data rate, and close proximity (e.g., personal area)wireless ad hoc network such as a Zigbee network. In certainimplementations, the communication networks can be any low-rate personalarea network, operation of which may be defined by the technicalstandard IEEE 802.15.4. In few implementations, the communicationnetwork can be any network implementing a Bluetooth Mesh, which is acomputer mesh networking standard based on Bluetooth Low Energy thatallows for many-to-many communication over Bluetooth radio.

Computing Device, and Generation of Insights and Rewards

The computing device 108 can use the data generated within the system100 to generate insights. Such generation of insights is now explained.

The sensors within the measuring device 104 can detect respectivefeatures. For example, the one or more weight sensors can weigh theproduct 102, the one or more motion sensors can detect a motion of theproduct 102, and one or more time sensors can observe a time consumed bythe weight sensor and/or the motion sensor. The motion sensor may detecta movement of the product 102 to generate motion data. In someimplementations, the sensor unit includes an accelerometer to detect themovement of the product 102 to, for example, confirm the usage of theproduct 102. The weight sensor may weigh the product 102 when theproduct 102 is placed on the stable condition after the movement andgenerate weigh data. The time sensor may observe the time consumed onthe weight sensor and the motion sensor to generate time consumed data.The time sensor may timestamp the usage of the product 102. The timesensor can be a clock or a timer. Optionally, the timestamp includesmorning, afternoon, evening and night. The timestamp may include thereal-time usage of the product 102.

In some implementations, the measuring device 104 may be used for asingle product 102. For example, the measuring device 104 may bedisposed or discarded after consumption or usage or the product 102. Inother implementations, the same measuring device 104 may be reused forseveral different products. For example, the measuring device 104 may beused to perform measurements for the product 102, and subsequently theconsumer or user may couple the measuring device 104 to another productso as to perform measurements for the other product. In someimplementations, the computing device 108 may permit the consumer oruser to couple a new product with the measuring device 104 only aftermeasurements of the product 102 have been completed or the product 102has been fully consumed (e.g. the computing device 108 may permitscanning a barcode of the new product and capturing the photograph (orvideo in some implementations) of the new product on a camera of thecommunication device 106 only after the measurements for the product 102have been completed). This advantageously avoids errors in measurementsfor different products by keeping measurements for different productsdiscrete. While measurements for different products are takenseparately, as explained above, in other implementations the computingdevice 108 may allow the measuring device 104 to be coupled to multipleproducts, whereby the measuring device 104 can include some processingcapability to organize the measurements for different productsseparately. In such cases, the processing by the measuring device 104prevents frequent back and forth of substantial amount of data over thecommunication network 114, which can reduce bandwidth usage and decreaselatency.

In a few implementations, the measuring device 104 includes a space fora label that can be manually stuck on the measuring device 104, or adigital label that can be programmed from any of an application,communication device 106, computing device 108, client device 110, anyother one or more computers, and/or a cloud platform.

The measuring device 104 transmits the weigh data, the motion data, thetime consumed data, location data, and any other related data of theproduct 102 to the computing device 108 through the communicationnetwork 114. The computing device 108 also receives the data (e.g. videoor audio) showing the consumption or usage of the product 102 along withthe feedback from the consumer or user (which can be in the form ofvideo, audio, or text such as responses to preset questions; which canbe superimposed on the data—e.g. video or audio—showing the consumptionor usage of the product 102 by the consumer or user).

Machine Learning to Generate Insights, Recommendations, and/or Rewards

The computing device 108 can input all of this data received from themeasuring device 104 and the communication device 106 to a trainedmachine learning model to generate the insights. The machine learningmodel may have been trained on historical weigh data, historical motiondata, historical time consumed data, and/or other similar data, all ofwhich can be of the consumer or user and/or other consumer or users ofsame or similar products. The machine learning model may have beentrained previously by and/or on the computing device 110 and/or anyother one or more devices.

The machine learning model that is trained and deployed to performmachine learning can be a supervised model (e.g. a model that involveslearning a function that maps an input to an output based on exampleinput-output pairs) or an unsupervised model (e.g. a model used to drawinferences and find patterns from input data without references tolabeled outcomes). The supervised model can be a regression model (e.g.model where output is continuous) or a classification model (e.g. modelwhere the output is discrete).

The regression model can be one or more of: (a) a linear regressionmodel (e.g. a model that finds a line or curve that best fits the data),(b) a decision tree model (e.g. a model that has nodes, where the lastnodes of the tree that are also referred to as leaves of the tree makedecisions, where the number of nodes can be increased to enhanceaccuracy of the decision making and number of nodes can be decreased toenhance speed to reduce latency), (c) random forest model (e.g. modelthat involves creating multiple decision trees using bootstrappeddatasets of the original data and randomly selecting a subset ofvariables at each step of the decision tree, where this modeladvantageously reduces the risk of error from an individual tree), (d) aneural network (e.g. a model that receives a vector of inputs, performsequations at various stages, and generates a vector of outputs), and/orthe like.

The classification model can be one or more of: (a) a logisticregression model (e.g. a model that is similar to linear regression butis used to model the probability of a finite number of—e.g.two—outcomes; for instance, a logistic curve or equation may be createdin such a way that the output values can only be between 0 and 1), (b) asupport vector machine (e.g. a model that finds a hyperplane or aboundary between two classes of data that maximizes the margin ordistance between the two classes), (c) naïve bayes model (e.g. a modelthat determines a class by implementing the bayes theorem).

The unsupervised learning models can be one or more of: (a) clusteringmodels (e.g. a model that involves the grouping, or clustering, of datapoints, wherein such models can involve various clustering techniquessuch as k-means clustering, hierarchical clustering, mean shiftclustering, and density-based clustering), and (b) dimensionalityreduction models (e.g. a model that eliminates or extracts features toreduce the number of random variables under consideration by obtaining aset of principal variables), and/or the like.

The computing device 108 can implement any of these machine learningmodels to generates insights based on data received from the measuringdevice 104 and the communication device 106. Some insights are specificto and beneficial for the consumer or user, and certain insights arespecific to and beneficial for a merchant (e.g. manufacturers,distributors, retailers, and/or the like) of the product. The insightscan include qualitative insights and quantitative insights.

The computing device 108 can (a) implement a rewards system to rewardthe consumer or user for tracking the consumption or usage of theproduct 102, (b) generate a report that will be helpful for an entity(e.g. merchant—such as manufacturers, distributors, retailers, and/orthe like—of the product 102), and (c) generate a report that will behelpful for the consumer or user. The reports can include respectiveinsights, which can be qualitative and/or quantitative in variousimplementations.

The rewards system can be a points based system to determine rewardpoints to the consumer or user for tracking his or her consumption orusage of the product 102. In various implementations, the computingdevice can allocate reward points to the consumer or user based on (a)usage of one or more devices for tracking consumption or usage of one ormore products, (b) using the communication device 106 for performingvarious activities (e.g. responding to various prompts in the form ofquestions, such as survey questions, or requests for performance oftasks, such as video, photo, and/or audio tasks), and/or the like. Thecomputing device 108 can also map the rewards points to one or morepayment means such as cash, gift cards, cryptocurrency, or the like.

The computing device 108 can generate one or more reports including thequalitative insights and the quantitative insights. For example, thecomputing device 108 can generate a report for the consumer or user thatincludes the insights specific to the consumer or user, and anotherreport for the entity (e.g. merchant-such as manufacturers,distributors, retailers, and/or the like—of the product) that includesthe insights specific to the entity.

The qualitative and quantitative insights may include the usage of theproduct 102 at various time periods. The report may include any of: agraphical representation of the usage of the product 102 over a periodof time, and/or a tabular column elaborating the usage of the product102 over the period of time. In some implementations, the period of timecan vary from a first time (e.g. week 1) to a subsequent or last time(e.g. week 52). In a few implementations, the report includes thegraphical representation of the consumption or usage of one or moreproducts used by the consumer or user. In certain implementations, thereport includes the graphical representation of the usage of oneparticular product. The computing device 108 generates report withqualitative and quantitative insights that reflect accurate usage and/orconsumption of the product 102 with less or no human intervention orerror. In some implementations, the computing device 108 generatesreport that includes the qualitative and quantitative insightscomprising the usage of one or more products by one or more consumers orusers and the timestamps to determine the usage behavior of the one ormore products by the one or more consumers or users.

Transmission of Report with Insights and Rewards to Communication Deviceand Client Device

The computing device 108 can transmit data characterizing the rewardsearned by the user of the product 102 to the communication device 106,which can output (e.g. display) the data for the user.

The computing device 108 can transmit the report specific to the entity(e.g. merchant—such as manufacturers, distributors, retailers, and/orthe like—of the product) to the client device 110. The report specificto the entity may not identify users whose consumption or usage isreported so as to ensure and protect user privacy. The report specificto the entity can however refer to different users anonymously withoutproviding any information that can compromise confidentiality or privacyof individual users. In some implementations, the report specific to amerchant can include (a) different products, which include the product102, specific to and associated with that merchant, (b) characteristicsof each product, (c) various analytical metrics associated with eachcharacteristic, (d) consumption of usage behavior of all users inaggregate or with a common feature (e.g. same geographic region, samebracket for income, same gender, same education level, and/or the like)for each product, and/or the like. Such report can advantageously enablethe entity (e.g. merchant) to assess their product campaigns, create newproducts, and make modifications to existing products, content ofproducts, manufacturing processes, advertising campaigns, distributionchannels, and/or any other purpose.

The computing device 108 can transmit the report specific to the user ofthe product 102 to the communication device 106. The report specific tothe user can indicate the consumption or usage behavior of the user forvarious products, including the product 102. For example, the report canspecify (a) the categories of products that the user has consumed orused (e.g. convenience products, shopping products, specialty products,and/or unsought products), (b) consumption or usage of products in eachcategory, (c) a quantity of consumption or usage of each product, and/orthe like. Such report can advantageously enable the user to make aninformed decision to modify consumption and/or usage behavior (e.g.habits).

Use of Data Platform (e.g. Software as a Service)

In some implementations, the computing device 108 may be integrated aswith the communication device 106 and/or the client device 110 as a dataplatform to provide services to clients. The data platform may beintegrated with the computing device 108 to provide services organizedby product category, country, potentially audience type/size, and/or thelike. An example of such data platform is a software as a service (SaaS)platform. In such cases, the computing device 108 can be a cloudcomputing server, which can provide services on demand such that theSaaS platform is also termed as an on-demand software.

In some implementations, the SaaS platform can have a multitenantarchitecture. In a multitenant architecture, a single version of theapplication facilitated by the computing device 108, with a singleconfiguration for hardware, network, operating system is used for allconsumers or users (which are also referred to as tenants within thescope of multitenant architecture). This architecture can beadvantageous over traditional software, where multiple physical copiesof the software—each potentially of a different version, with apotentially different configuration, and often customized—may beinstalled across various customer sites, because SaaS allows theunderlying device on which SaaS is used (e.g. communication device 106and/or the client device 110) to be a thin client, which can be alow-performing computer that has been optimized for establishing aremote connection with a server-based computing environment.

While a multitenant architecture is described, in other implementationsthe SaaS platform can implement other mechanisms such as virtualization.Virtualization can be creation of a virtual machine that acts like areal computer with an operating system. Software executed on a virtualmachine can be separated from the underlying hardware resources.

While the data platform is described above as a SaaS platform, in someimplementations the data platform can be an infrastructure as a service(IaaS), a platform as a service (PaaS), a desktop as a service (DaaS),managed software as a service (MSaaS), mobile backend as a service(MBaaS), datacenter as a service (DCaaS), information technologymanagement as a service (ITMaaS), and/or the like.

Some Examples of Product

Some examples of the product 102, as described herein, include cleaningliquids, wipes, sprays, floor cleaning pads, body-wash, shampoo,hand-soap, sauce cans, beverages, alcohols and/or the like. The product102 can be categorized as customer packaged goods (CPG), fast-movingconsumer goods (FMCG), and/or food and beverages (F&B). The CPG and F&Bmay include categories that includes dish care (e.g. dishwashing liquid,dishwasher pods, dishwasher spray and/or dishwasher detergent),household cleaning (e.g. surface wipes & sprays, all-purpose sprays, airfreshening sprays, liquid floor cleaners and/or pad based systems),laundry & fabric care (e.g. laundry liquid, detergent, pods, fabricrefresher spray, fabric softener and/or dryer sheet), personal cleaning(e.g. skin care, body wash, moisturizers, hair care,shampoo/conditioner, hand soap and/or shaving gel), family care (e.g.paper towels and/or facial tissues), fragrance (e.g. perfumes and/ordeodorants), feminine care, oral care (e.g. mouthwash and/ortoothpaste), personal health, alcohol and/or spirits, baking products,beverages, biscuits and/or cookies, cereals, chocolates, dairy products,fruit, gum and/or candy, ice cream, meals, pasta, pet food, snacks,spices, vegetables, yogurt, and/or the like. The application on thecommunication device 106 may categorize the product 102 into thesecategories, or allow the user to perform such categorization.

Additional Details for Measuring Device

FIG. 2 illustrates one example of the measuring device 104, according tosome implementations described herein. The measuring device 104 caninclude a weight sensor 202, a motion sensor 204, a time sensor 206 anda communication module 208. The weight sensor 202 weighs the product 102when the product 102 is placed on the measuring device 104 and generatesthe weight data of the product 102. The weight sensor 202 can include atleast one load cell (e.g. any number of load cells, such as four loadcells), which is a transducer that converts force into a measurableelectrical output that indicates weight. Any load cell described hereincan be a hydraulic load cell, pneumatic load cell, strain-gauge loadcell, piezoelectric load cell, inductive and reluctance load cell,magnetostrictive load cell, capacitive load cell, and/or the like. Anyload cell may have any shape or size. In certain implementations, theweight sensor 202 can weigh the product 102 automatically if (a) theproduct 102 is in a stable condition, (b) the product 102 is used withina preset period of time (e.g. 1 hour, 2 hours, 6 hours, 12 hours, 24hours, or any other time period), (c) the product is used regularly(e.g. at least twice, at least thrice, or so on) over a preset period oftime, and/or (d) every time the product is taken away from the measuringdevice 104 (which may indicate usage of the product) and/or placed backon the measuring device 104. The motion sensor 204 can detect the motionof the product 102 to generate the motion data. For example, the motionsensor 204 detects the movement and/or direction of the movement of theproduct 102 to generate the motion data. The motion sensor 204 may be anaccelerometer. The time sensor 206 detects the time consumed on theweight sensor 202 and the time consumed on the motion sensor 204 togenerate the time consumed data. The time consumed data can include atime and a date. In some implementations, the time sensor 206 cantimestamp one or more of the movement of the product 102, the length oftime of movement of the product 102, a time when the weight sensor 202weighs the product 102, and/or the like.

While the measuring device 104 is shown as including the weight sensor202, motion sensor 204, and time sensor 206, in some implementations,the measuring device 104 can additionally or alternately include othersensors, such as location sensors, a temperature sensor, proximitysensor, infrared sensor, ultrasonic sensor, humidity sensor, tiltsensor, level sensor, touch sensor, and/or the like. The locationsensors can include (a) a GPS sensor that can detect the geographicalcoordinates of the measuring device (e.g. detect a particular addresssuch as a house or building on a map), and/or (b) an internal locationsensor that can detect the particular location within a specific address(e.g. detect specific room within a house, a specific unit or apartmentwithin a building, a shop within a shopping mall, an exhibit locationwithin a conference, a room within a museum, and/or the like). To trackthe internal location using the internal location sensor, beacons can beinstalled in the address location (e.g. house, building, mall, ormuseum), and such beacons can sense proximity of the internal locationsensor within the measuring device 104 from each of the beacons ateither preset intervals of time or in real-time. In someimplementations, there may be a one-time mapping of the beacons usingthe communication device 106. Using the proximity between the measuringdevice 104 and each of the beacons, the internal location sensor canestimate an approximate location of the measuring device 104, which canbe beneficial in learning the specific internal location of the product102 when the measuring device 104 is physically coupled (e.g. affixed orplaced adjacent) to the product 102. The beacons can be Bluetooth lowenergy (BLE) beacons and/or IEEE 802.15.4 or low-rate wireless personalarea network (LR-WPAN) beacons. In some implementations, there may notbe a need for external beacons as the internal location sensors of themeasuring device may work as a beacon. While beacons are described asbeing used to detect the internal location, in other implementations,the internal location sensor can implement other technologies to detectthe internal location, such as WiFi, magnetic field detection, nearfield communication, gyroscope and accelerometer, ultra-wideband, and/ormicro-electro-mechanical systems (MEMS) sensors, as explained below.

WiFi can be used in a similar way as BLE beacons, but this technologymay require an external power source and additional equipment. In someimplementations, the equipment may be expensive. In some suchimplementations, the BLE beacon technology may be preferred over theWiFi technology to identify an internal location of the measuring device104. The WiFi technology can be advantageous in some implementations ascompared to the BLE beacon technology because the signal in the WiFitechnology can be stronger, and can cover more distance. In the magneticfield detection, the internal location sensor within the measuringdevice 104 can include a compass for indoor positioning, afingerprinting technology can be used to map the magnetic fields on thevenue and the measuring device 104 can use that map to find the indoorlocation of the measuring device 104. The magnetic field detectiontechnology may not be implemented in certain circumstances where themagnetic fields indoor are stable. The near field communication (NFC)technology includes small chips that do not require a power source, andthe internal location sensor within the measuring device 104 detectseach chip to read the serial number of the chip if the measuring device104 is within a specific distance (e.g. 30 centimeters) away from thechip. The NFC technology is advantageous in locations where the product102 can be stored in a small space so that detections can be made withinthe specific distance such as 30 centimeters. A gyroscope is a devicefor measuring or maintaining orientation, based on the principles ofconservation of angular momentum, and this orientation information canbe used for even more precise positioning of the measuring device 104.Ultra-wideband (UWB) is a most precise method of detecting indoorpositions. Under the UWB, UWB anchors are placed in the corners of avenue up to a preset distance (e.g. 25 meters) apart, and a UWB locatortag is attached to an asset to be tracked. The UWB locator tag can sendradio signal pulses within a particular frequency range (e.g. between3-7 GHz), which the UWB anchors can use to position the tag with some(e.g. up to 30 centimeters) accuracy in a three dimensional space andwith positioning updates up to every preset time period (e.g. every 50milliseconds).

The measuring device 104 can transmit the weigh data, the motion data,the time consumed data, and any other sensor data to the computingdevice 108 either directly or via the communication device 106, usingthe communication module 208. In certain implementations, thecommunication module 208 transmits the weigh data, the motion data andthe time consumed data to the computing device 108 with thecommunication network 114. The measuring device 104 may determine theweigh data, the motion data and the time consumed data automaticallywhen at least one of: the product 102 is in a stable condition, theproduct 102 is not used and/or the product 102 is used.

The term module, as noted herein, can include software instructions andcodes to perform a designated task or a function. A module as usedherein can be a software module or a hardware module. A software modulecan be a part of a computer program, which can include multipleindependently developed modules that can be combined or linked via alinking module. A software module can include one or more softwareroutines. A software routine is computer readable code that performs acorresponding procedure or function. A hardware module can be aself-contained component with an independent circuitry that can performvarious operations described herein.

Communication Module Within Measuring Device

FIG. 3 illustrates the communication module 208 of the measuring device104 that is communicatively connected to the computing device 108,according to some implementations described herein. The communicationmodule 208 of the measuring device 104 is communicatively connected tothe computing device 108 through the communication network 114. Thecommunication module 208 includes at least one of a Wi-Fi module 302, aBluetooth module 304, and/or a SIM module 306 to transmit the weighdata, the motion data and the time consumed data from the measuringdevice 104 to the computing device 108 through the communication network114.

The SIM module 306 may include an IoT SIM card to provide requiredconnectivity for transmitting the weigh data, the motion data and thetime consumed data to the computing device 108 automatically. In a fewimplementations, the measuring device 104 transmits the weigh data, themotion data and the time consumed data to the computing device 108automatically. In some implementations the measuring device 104transmits the weight data, the motion data, and the time consumed datato the communication device 106 though the communication network 114,and then the data may be further transferred to the computing device 108through the communication network 114.

While the communication module 208 is described as including a Wi-Fimodule 302, a Bluetooth module 304, and a SIM module 306, in otherimplementations the communication module 208 may include additional oralternate modules that can enable communication over a respectivecommunication network.

Another Example of Measuring Device

FIG. 4 illustrates another example of the measuring device 104,according to some implementations described herein. The measuring device104 includes the weight sensor 202, the motion sensor 204, the timesensor 206, the communication module 208, an indicator (e.g. LEDindicator) 402 and a local storage module 404. The LED indicator 402indicates when the weight sensor 202, the motion sensor 204 and the timesensor 206 determines the weigh data, the motion data and the timeconsumed data respectively. The LED indicator 402 may indicate the weighdata to show the measurement of the product 102. Using LEDs for theindicator 402 can be beneficial for reasons such as: (a) LEDs are energyefficient, (b) LEDs require a low maintenance, (c) LEDs have a longlifespan (e.g. lifespan exceeding 10 years) because there is no filamentto burn out, (d) the upfront costs of LED lighting are low, (e) LEDsemit almost no heat or ultraviolet (UV) rays, and (f) LEDs are usuallynot hot to touch, making them safe to handle.

While the indicator 402 is described as an LED indicator, in otherimplementations any other light-based indicator can be used, such asincandescent lamp, halogen lamp, fluorescent lamp, compact fluorescentlamp, high-pressure sodium lamp, and low-pressure sodium lamp. While theindicator 402 is described as a light-based indicator (i.e. indicatorthat emits light), in other implementations, the indicator can be anaudio indicator (e.g. sound alarm) or an audio-visual indicator (e.g.alarm that can include LEDs to generate light and audio circuitry togenerate sound).

The local storage module 404 can, in some implementations, store theweigh data, the motion data and the time consumed data. The localstorage module 404 can be one or more of: hard disc drives (HDDs), solidstate drives (SSDs), or external storage devices such as thumb drives ordiscs. In a particular example, the local storage module 404 can be anon-volatile memory card (e.g. SD card). Having the local storage module404 in the architecture can be beneficial for implementations where theweigh data, the motion data and the time consumed data needs to beprocessed by the measuring device 104 (e.g. to organize the data, or toprocess the data so as to remove redundancies) before transmitting allof that data to the computing device 108 because such local storageallows a quicker access of data, which prevents upload and download ofdata, including redundant data, had the storage been remote from themeasuring device 104. Having the local storage module 404 in thearchitecture can be further beneficial in some implementations where thedata syncs to the computing device 108 (e.g. cloud computing server)only once or few times daily, as such local storage allows the measuringdevice 104 to store the data and transmit only at certain intervals,thereby preserving and optimizing bandwidth. Such local storage is alsobeneficial when the communication network or communication apparatus(e.g. subscriber identification module (SIM) card within thecommunication device 106) is temporarily inoperable or malfunctioning,as in such situations the local storage can store data until thecommunication apparatus is able to synchronize with the communicationdevice 106.

The measuring device 104 may include a control key (which can also bereferred to as an on/off control key) to activate (i.e. switch on) ordeactivate (i.e. switch off) the measuring device 104. When themeasuring device 104 is activated (i.e. switched on), the measuringdevice 104 may determine the weight data, the motion data and the timeconsumed data automatically. The measuring device 104 may be powered bya battery, and may be configured to consume low power. The battery canbe primary battery (i.e. designed to be used until exhausted of energy)or rechargeable battery (i.e. can be recharged by virtue of having theirchemical reactions reversed by applying electric current to the cell).In some implementations, the battery can include one or more ofelectrochemical cells, such as galvanic cells, electrolytic cells, fuelcells, flow cells, and/or voltaic piles. In a few implementations, themeasuring device 104 may be powered by electric power extracted (e.g.received) from a power outlet.

In some implementations, the measuring device 104 automaticallydeactivates (i.e. switches off) when not in use, and activates (i.e.switches on) when the product 102 is used for a while, in the period oftime, includes a schedule to weight the product 102 at a certainfrequency and/or upon motion of the product 102. In the case of ascheduled frequency, the period of time may be any preset time, such as1 hour, 2 hours, 4 hours, 6 hours, 12 hours, 18 hours, 24 hours, or anyother value. In some implementations, only the components that may notbe required (e.g. components required for WiFi or other communication)may be deactivated (e.g. powered or switched off) to save power, whileother components such as the sensors (e.g. weight sensor 202, motionsensor 204, time sensor 206, and/or the like) may go into a sleep modebut can be instantly activated upon sensing a particular (e.g.respective threshold-based) change in weight, motion, or time.

Generation of Notifications To be Displayed on Communication Device

FIG. 5 illustrates an exemplary view of the measuring device 104 that iscommunicatively connected to the computing device 108 to trigger anotification on the communication device 106, according to someimplementations described herein. The measuring device 104 can transmitthe weigh data, the motion data and the time consumed data to thecomputing device 108 continuously and/or automatically. When the product102 is finished, the weight sensor 202 may transmit zero-reading data tothe computing device 108. The computing device 108 receives thezero-reading data and triggers a notification in the mobile applicationof the communication device 106 to check whether the product 102 is outof stock. The notification may enable the consumer or user to attach thenew product to the measuring device 104. In some implementations, thenotification is triggered continuously until the weight sensor 202determines weigh data. For example, if the consumer or user forgets tochange the product 102, the computing device 108 triggers a notificationto attach the new product with the measuring device 104.

When the new product is attached to the measuring device 104 withoutscanning a barcode of the new product, the significant change in theweight may enable the computing device 108 to trigger a notification toconfirm the measuring device 104 has been installed on the new product.When the measuring device 104 is not attached with any products, thecomputing device 108 may trigger a notification to remind the consumeror user to attach the measuring device 104 with the new product.

The consumer or user may set preferences in the mobile application ofthe communication device 106 to any of: receive a notificationmentioning the product 102 is low and/or automatically re-order/purchasethe product or add the product in a shopping list. The mobileapplication of the communication device 106 may be used as a homemanagement system. The computing device 108 (and/or, in someimplementations, the communication device 106) may provide additionalvalue in the form of discounts/deals on new and/or available productsand also provide recommendations on new and/or alternate products. Insome implementations, the recommendations can include any of: paidadvertisements or promotions and/or tailored recommendations based onoverall product preferences of a consumer or user and/or all productsbeing tracked or measured by a user and/or behavior of consumption orusage of the product 102 by the consumer or user and/or all otherconsumers or users of the product 102 and/or other consumers or usersthat are similar to the consumer or user. The recommendations can bebased on actual consumption or usage behavior, and therefore areunbiased as compared to reviews that can be subjective. In someimplementations, such content (e.g. advertisements, promotions, ordeals) can be delivered at a time when there is only a certain threshold(e.g. percentage) of product 102 remaining (i.e. rest of the product 102has been consumed or used). In addition to advertisements or promotions,there may be product placement sponsored by merchants to see howconsumption or usage behavior of the user changes if a new product isintroduced in their environment (e.g. household or business) where theirmeasuring devices 104 are placed.

Attachment Mechanism for Connecting Measuring Device with Product

FIG. 6 illustrates the product 102 connected with the measuring device104, according to some implementations described herein. The measuringdevice 104 includes a connector 602 that can connect (e.g. attach) themeasuring device 104 with the product 102. The connecter 602 may includeattachment means including gluing, knitting or threading, welding,magnetic attachment, fastening, taping, coupling using one or more ofscrews or nails, twisting and fitting two or more components untilfirmly attached (e.g. locked), pressing one component over another untilfirmly attached to each other (e.g. locked with respect to each other),and/or any other one or more attachment mechanisms.

System for Measurements related to Consumption or Usage of MultipleProducts

FIG. 7 illustrates an exemplary view of one or more products 102A-Ncommunicatively connected with one or more measuring devices 104A-N todetermine the consumption or usage behavior of the one or more products102A-N by the consumer or user, according to some implementationsdescribed herein. The one or more products 102A-N connects with the oneor more measuring devices 104A-N either through one or more connectorsor without any connector (e.g. the one or more products 102A-N can beconnected by simply being placed on respective one or more measuringdevices 104A-N). The one or more measuring devices 104A-N transmits theweigh data, the motion data and the time consumed data of the one ormore products 102A-N to the computing device 108 via the communicationnetwork 114. The computing device 108 determines the consumption orusage behavior of the one or more products 102A-N by the consumer oruser based on the weigh data, the motion data and the time consumed dataassociated with the one or more products 102A-N. The computing device108 transmits/provides the consumption or usage behavior of the one ormore products 102A-N by the consumer or user to the client device 110.

Example User Interface of Computing Device

FIG. 8 illustrates an exemplary view of a graphical user interface 800of the computing device 108, according to some implementations describedherein. The graphical user interface 800 of the computing device 108illustrates sessions of one or more consumers or users, consumption orusage of the one or more products 102A-N by the one or more consumers orusers and surveys or other activities done by the one or more consumersor users. The sessions may include a participant name of the one or moreconsumers or users and/or a location of the one or more consumers orusers. In some implementations, the sessions include a video survey toknow about the one or more consumers or users. The video survey mayinclude questions that includes “What is your first name and where doyou live?”, “How often do you purchase this product?” and the like aswell as tasks that include “Show us how you use this product”, “Tell usyour thoughts on this new concept” and the like. The video may berecorded by the communication device 106, and the communication device106 can transmit the recorded video to the computing device 108. In someimplementations, the computing device 108 transcripts the recorded videointo texts. The recorded video may be filtered by any of:tasks/questions, audio keywords and/or visual objects/scenes. Therecorded video may include a self-moderated interview of the one or moreconsumers or users who used the one or more products 102A-N.

While various specific activities are shown in FIG. 8 , in someimplementations there can be data for sessions of any activity to beperformed by a consumer or user such as video activity, survey activity,photo activity, weigh-in activity, sensor activity, audio activity,barcode activity, receipt capture activity, screen recording activity,and/or the like. In some examples, each consumer or user may be requiredto perform multiple activities over a period of time.

Example User Interface of Computing Device

FIG. 9 illustrates an exemplary view of a graphical user interface 900of the computing device 108, according to some implementations describedherein. The graphical user interface 900 of the computing device 108 caninclude tasks/questions for initializing the product 102. The product102 may be a dishwashing liquid. The tasks/questions may include thescanning of the product 102 using the communication device 106, weighingof the product 102 using the measuring device 104, and/or entering areading of the measuring device 104. In certain implementations, themeasuring device 104 may automatically provide the reading to thecomputing device 108 (either directly or through the communicationdevice 106), and there may not be a task/question corresponding toentering such reading of the measuring device 104 and thus the user maynot be required to manually enter the reading of the measuring device104. In some implementations, the communication device 106 scans thebarcode of the product 102 and the computing device 108 determinedetails of the product 102 based on the barcode of the product 102. Thedetails of the product 102 may include a barcode number, a barcode type,manufacturer, a category, a brand, an UPC detail, a base size, a subbrand, a main category, a collection, a form and/or other availablebarcode data. While the graphical user interface 900 is specific to aparticular product (i.e. dishwashing liquid), in other implementationsthe graphical user interface 900 may be generated for any product (e.g.any type of product).

Example Report for User as Displayed on User Interface of Client Device

FIG. 10 is a graphical representation 1000 of a report that depictsweekly (and in some implementations, daily, hourly, particular day ofany week, weekday, weekend, or any time range) consumption of theproduct 102, according to some implementations described herein. Thegraphical representation 1000 of the report includes the weeklyconsumption or usage of the product 102 over a period of time. Theperiod of time may include week 1 to week 9. While the period of time isshown as 9 weeks, in some implementations the length of time can be anyamount of time depending on the needs of a particular project, and/orneeds and/or desire of the entity for whom insights are being generated.For example, in some variations, the length of time can be 2 weeks, 6weeks, 12 weeks, 20 weeks, 6 months, 1 year, 2 years, 3 years, or anyother length of time. The graphical representation 1000 of the reportincludes a Y-axis that shows the usage of the product 102 by a consumeror user and an X-axis that shows the period of time in weeks. Thegraphical representation 1000 includes one or more points to representthe usage of the product 102 by the consumer or user from second week toninth week. While the graphical representation 1000 is described asbeing presented on the client device 110, in some implementations thegraphical representation 1000 can additionally or alternately berepresented on the computing device 108. Optionally, the graphicalrepresentation 1000 can be shown on the communication device 106. Whilethe graphical representation 1000 is specific to a particular productcategory (i.e. dishwashing liquid), in some implementations thegraphical representation 1000 may be alternately or additionally begenerated for any product (e.g. dishwashing liquid by a specific brand).

Example Report for User as Displayed on Client Device

FIG. 11 is a graphical representation 1100 of a report that depictsaverage weekly consumption, average weekend consumption, average weekdayconsumption of the product 102 or the category of products that product102 belongs to, according to some implementations described herein.While the depiction of average weekly consumption, average weekendconsumption, and average weekday consumption is described, in someimplementations, the techniques can be extended to monitor averages ofconsumption on a daily basis, hourly basis, particular day of any week,or monthly basis. The graphical representation 1100 of the reportincludes the average weekly consumption, average weekly consumptionindex week prior, the average weekend consumption, the average weekdayconsumption, number of weigh-ins in a same product, number of weigh-insin a new product, number of out of stocks, and total number of weigh-insfor X number of weeks. While the graphical representation 1100 isdescribed as being presented on the client device 110, in someimplementations the graphical representation 1100 can additionally oralternately be represented on the computing device 108. Optionally, thegraphical representation 1100 can be shown on the communication device106.

While the period of time is shown as 9 weeks, in some implementationsthe length of time can be any amount of time depending on the needs of aparticular project, and/or needs and/or desire of the entity for whominsights are being generated. For example, in some variations, thelength of time can be 2 weeks, 6 weeks, 12 weeks, 20 weeks, 6 months, 1year, 2 years, 3 years, or any other length of time.

Example User Interface as Displayed on Client Device

FIG. 12 illustrates an exemplary view of a graphical user interface 1200of the client device 110, according to some implementations describedherein. The graphical user interface 1200 includes tasks/questions forinitializing any of: a second product, a third product and the like.While the graphical representation 1200 is described as being presentedon the client device 110, in some implementations the graphicalrepresentation 1200 can additionally or alternately be represented onthe computing device 108, or optionally on the communication device 106.

Example Report for Merchant Displayed on User Interface of Client Device

FIG. 13 is a graphical representation 1300 of a report that depictsweekly (and in some implementations, daily, by time of day, day of week,or the like) consumption details of the one or more products 102A-N orcategories of products by the consumer or user or groups of consumers orusers, according to some implementations described herein. The graphicalrepresentation 1300 of the report includes a Y-axis that showsconsumption or usage of the one or more products 102A-N and an X-axisthat shows the period of time in weeks. The one or more products 102A-Nincludes a fabric refresher spray 1302, constant non energized airfreshening products 1304, air freshening electrical plug-ins 1306, anair freshening spray 1308, cleaning system for dusting surfaces 1310,disposable dry floor cleaning wipes 1312, disposable wet floor cleaningwipes 1314, a kitchen cleaning spray 1316, sanitizing surface wipes1318, all-purpose cleaning spray 1320, a floor cleaner 1322 and adishwashing liquid 1324. Optionally, the graphical representation 1300can be shown on the communication device 106.

While the period of time is shown as 9 weeks, in some implementationsthe length of time can be any amount of time depending on the needs of aparticular project, and/or needs and/or desire of the entity for whominsights are being generated. For example, in some variations, thelength of time can be 2 weeks, 6 weeks, 12 weeks, 20 weeks, 6 months, 1year, 2 years, 3 years, or any other length of time. Further, while thegraphical representation 1300 is specific to particular products asdescribed above, in other implementations the graphical representation1300 may be generated for any type or number of products.

Example Report for Merchant as Displayed on User Interface of ClientDevice

FIG. 14 is a graphical representation 1400 of a report that depictsweekly (and in some implementations, daily, by time of day, day of week,or the like) consumption of the one or more products 102A-N by theconsumer or user, according to some implementations described herein.The graphical representation 1400 of the report includes the weeklyconsumption of the one or more products 102A-N in grams usage. While thegraphical representation 1400 is specific to particular products shownin the drawing, in other implementations the graphical representation1400 may be generated for any type or number products.

While various graphical representations are shown in FIGS. 8-14 , thesegraphical representations are merely exemplary, and the representationscan be varied or alternative representations can be generated based ondata collected and tracked, needs and/or desires of entities for whominsights are generated, and/or any other one or more reasons.

Button Device For Quantifying Consumption or Usage of Product

FIG. 15 is an exemplary button device 1502 to analyze the product 102,according to some implementations described herein. The button device1502 includes a button 1504 that can be pressed when the consumer oruser consumes or uses the product 102. In some implementations, thebutton device 1502 detects the consumption or usage of the products 102when the consumer or user manually presses the button 1504 while theconsumer or user using the product 102. The button device may generatebutton pressing data when the consumer or user manually presses thebutton while the consumer or user using the product 102 and transmit thebutton pressing data to the computing device 108 to determine theconsumption or usage behavior of the product 102 by the consumer oruser. The button device 1502 may be fixed with the product 102 or thedoor/opening of a cabinet, fridge, or other appliances for automaticoperation of the button device 1502. In an example implementation, thebutton device 1502 is placed inside the fridge. When the fridge isopened, the button 1504 will be activated (e.g. released) and when thefridge is closed, the button 1504 will be deactivated (e.g. pressed). Insome implementations, the button device 1502 may include controlconfigurations that includes a long press, a short press, a double pressand/or a triple press and the like.

Although a button device 1502 is described for quantifying (e.g.counting) consumption or usage of the product 102, in someimplementations the measuring device 104 can also or alternately performsuch quantification. An example where a button device 1502 is used canbe the button device 1502 determining a number of times a user hasshaved in response to the user manually pressing the button each timethey shave. An example where the measuring device 104 is used can be themeasuring device 104 (e.g. coaster), on which shaving cream is placed,determining, using a sensor (e.g. weight sensor), amount of shavingcream that was used and in turn also determining whether the associatedactivity (i.e. the entire process of shaving) was completed.

Example Weighing Device to Weigh Products

FIG. 16 is an exemplary weighing device 1602 to determine weigh data ofthe one or more products 102A-N, according to some implementationsdescribed herein. The one or more products 102A-N may be placed on theweighing device 1602 to determine the weigh data of the one or moreproducts 102A-N. While the weighing device 1602 is shown as beingrectangular, in another implementation the weighing device 1602 can becircular (e.g. in the form of a coaster). In yet other implementations,the weighing device 1602 can have any other shape, such as oval, polygonwith any number of sides, triangular, any irregular shape, or the like.The weighing device 1602 can display the weight on an optional display1604, which can be one or more of a liquid crystal display (LCD),electroluminescent display (ELD), light-emitting diode (LED) display,plasma display panel (PDP), quantum dot (QD) display, and/or the like.In some implementations, the weighing device 1602 may not have a displaysuch as the display 1604.

Example Method to Generate Insights

FIG. 17 is a flow diagram that illustrates a method performed by thesystem that generates insights on the behavior of consumption or usageof the product 102 by the consumer or user, according to someimplementations described herein. At step 1702, the computing device 108can be initialized by scanning the barcode of the product 102 and paringthe measuring device 104 with the product 102 using the communicationdevice 106. At step 1704, the computing device 108 can be activated inresponse to paring the product 102 with the measuring device 104. Atstep 1706, the weigh data of the product 102 can be determined by theweight sensor 202, the motion data of the product 102 is determined bythe motion sensor 204, and the time consumed data on the weight sensor202 and the motion sensor 204 is determined by the time sensor 206. Atstep 1708, the communication network 114 can be enabled between themeasuring device 104 and the computing device 108 to transmit the weighdata, the motion data and the time consumed data. At step 1710, a reportcan be generated on the computing device 108 to determine theconsumption or usage behavior of the product 102 by the consumer or userbased on the weigh data, the motion data and the time consumed data.

Example Measuring Device—Coaster

FIGS. 18-23 illustrate different views of an example of a measuringdevice 104 in the form of a coaster 1800.

FIG. 18 illustrates a top view of coaster 1800. The coaster 1800 canhave female coupling portions (e.g. grooves) 1802 that can be used tocombine the coaster with male coupling portions of other apparatuses,such as the sleeve shown in FIGS. 24-29 to grip (e.g. by firmly holding)the product 102 when placed on the coaster 1800. In otherimplementations, the coaster 1800 can include binding or constrictingapparatus (e.g. clamps; not shown) to grip (e.g. by firmly holding) theproduct 102 when placed on the coaster 1800. Although female couplingportions 1802 are described, in some implementations, the coaster 1800may not need to be combined with other apparatuses such as the sleeve,and thus may or may not have such female coupling portions 1802. Whenmultiple coasters 1800 are packaged together (e.g. ten coasters packagedtogether), the package may contain only some sleeves (e.g. threesleeves) because a coaster 1800 would connect with a sleeve only whenthere is a need for the circuitry within the sleeve (e.g. when there isa need to detect location of the product 102); thus only some coasters1800 (e.g. three or four of the ten coasters 1800 in the package) mayuse the female coupling portions 1802. In such package, one of thecoasters 1800 can be a hub, and other coasters 1800 can be spokes, wheresuch hub and spokes are configured to be arranged in a hub and spokearchitecture (as described below, such as in FIG. 46 ).

FIG. 19 illustrates a side view of the coaster 1800. The coaster 1800includes anti-slip apparatus 1804 that prevents the coaster 1800 fromslipping on a surface. The anti-slip apparatus 1804 can be made ofanti-slip material such as particular types of rubber, foam, polyester,fabric, and/or the like. In some examples, the anti-slip apparatus 1804can be rubber stoppers or rubber pads. Although four anti-slip apparatus1804 are shown in the drawings, in other implementations there can beany other number of anti-slip apparatus 1804.

FIG. 20 illustrates a bottom view of the coaster 1800. The coaster 1800can include fastening apparatus 1806 (e.g. screws) that can combinemultiple layers of the coaster 1800 or combine the coaster 1800 withother one or more apparatuses. Although screwing is described forcombination, in some implementations other combination means can be usedsuch as gluing, knitting or threading, welding, taping, coupling usingone or more of screws or nails, twisting and fitting two or morecomponents until firmly attached (e.g. locked), pressing one componentover another until firmly attached to each other (e.g. locked withrespect to each other), and/or any other one or more attachmentmechanisms to combine materials or apparatuses. The coaster 1800 caninclude a power button 2002 that can be used to activate or deactivatethe coaster 1800.

FIG. 21 illustrates a front view of the coaster 1800. The coaster 1800can include a port 1808 for charging the apparatus. The coaster 1800 caninclude an indicator (e.g. light emitting diode indicator) 1810 that canindicate the status of charging. For example, the indicator can displaya red light when the battery of the coaster 1800 is low (e.g. less than20%), a yellow light when the battery is medium (e.g. between 20% and70%), and a green light when the battery is high (e.g. 70% or more). Insome implementations, the indicator 1810 can additionally generate alighted notification when the coaster 1800 is being activated (i.e.turned on), deactivated (i.e. turned off), or being used. While threelevels of indicators are described, in certain implementations there maybe any other number of levels, each being represented by a respectivecolor.

While a charging port of the coaster 1800 is displayed, in someimplementations, the coaster 1800 may have other ports that allow thecoaster 1800 to communicatively couple with some devices (e.g. computer,or peripheral devices such as mouse, keyboard, monitor or display unit,printer, speaker, flash drive, and/or the like) or the communicationnetwork. The ports can include one or more of: (a) a serial port, whichcan be used to couple the coaster 1800 with external modems or somecomputer mouse devices, (b) a parallel port, which can be used to couplethe coaster 1800 with scanners or printers, (c) a PS/2 port, which canbe used to couple the coaster 1800 with some computer keyboards ormouse, (d) a universal serial bus (USB) port, which can be used tocouple the coaster 1800 with external USB devices such as external harddisk, printer, scanner, mouse, keyboard, or the like, (e) a videographics array (VGA) port, which can couple a display on the coaster1800 to a video card, (f) a power port-which can vary for differentconnectors, which can be a universal serial bus (USB) connector, such asa USB-A, USB-B, USB-C, micro-USB, lightning cable, and such USB can haveany speed standards such as USB 1.x, 2.0, or 3.x—which can be used toreceive a power cable or any other charging apparatus to charge a batterwithin the coaster 1800, a firewire port, which can couple the coaster1800 to data equipment such as camcorders or video equipment, (g) amodem port, which can be used to couple the coaster 1800 with thecommunication network, (h) an Ethernet port, which can connect thecoaster 1800 to a communication network (e.g. internet), or any otherport.

FIG. 22 illustrates a top perspective view of the coaster 1800.

FIG. 23 illustrates a bottom perspective view of the coaster 1800.

Example Measuring Device—Sleeve With Coaster(s)

FIGS. 24-29 illustrate different views of an apparatus 2400 that formsthe sleeve of a measuring device 104 and that is configured to beattached to a coaster 1800 to form the measuring device 104.

FIG. 24 illustrates a top view of the apparatus 2400. The apparatus 2400includes a gripping device 2402 that is configured to move along thearea 2404 to firmly grip the product 102 (as further clarified in FIG.28 ).

FIG. 25 illustrates a side view of the apparatus 2400. The apparatus2400 has male coupling portions 2502 that can couple with femalecoupling portions 1802 shown in FIGS. 18, 19, and 21-23 .

FIG. 26 illustrates a front view of the apparatus 2400.

FIG. 27 illustrates a bottom view of the apparatus 2400. The apparatus2400 can optionally include a quick release button 2702 that can be usedto mechanically uncouple (e.g. unclamp) the product 102 from theapparatus 2400. The apparatus 2400 further includes fastening apparatus(e.g. screws) that can combine multiple layers of the apparatus 2400and/or anti-slip apparatus that prevents the apparatus from slipping.Such fastening apparatus (e.g. screws) and additional or alternativeanti-slip apparatus are collectively referenced as 2704. Althoughscrewing is described for combination, in some implementations othercombination means can be used such as gluing, knitting or threading,welding, taping, coupling using one or more of screws or nails, twistingand fitting two or more components until firmly attached (e.g. locked),pressing one component over another until firmly attached to each other(e.g. locked with respect to each other), and/or any other way tocombine materials or apparatuses.

FIG. 28 illustrates a top perspective view of the apparatus 2400.

FIG. 29 illustrates a bottom perspective view of the apparatus 2400.

FIGS. 30 and 31 illustrate different views of a measuring device 104formed by attaching the apparatus 2400 of FIGS. 24-29 with the coaster1800 of FIGS. 18-23 . The coupling is performed by coupling malecoupling portions 2502 of the apparatus 2400 with female couplingportions 1802 of the coaster 1800.

Example Measuring Device—Tray With Coaster(s)

FIGS. 32-34 illustrate different views of a tray 3200 of a particularmeasuring device 104 that is made operable by coupling (e.g. attaching)the tray 3200 with one or more coasters 1800. The tray 3200 can bebeneficial where larger or heavier items need to be weighed or measured,such as paper towels, toilet paper, diapers, pet food, or the like.While the drawings show each tray 3200 as being coupled to two coasters1800, in some implementations, each tray 3200 may be configured to becoupled to any other number (e.g. 1, 3, 4, 5, 6, or so on) of coasters1800. In certain implementations, the number of coasters 1800 to becoupled to a single tray 3200 may depend on the size (e.g. diameter orarea) of the tray 3200 and/or the size (e.g. diameter or area) of eachcoaster 1800.

In some variations, a hardware component (which can also be referred toas a hardware module), which has all electrical circuitry of the coaster1800, can be inserted into various other form factors such as a tray. Insuch implementations, one or more load cells (e.g. weight sensors) ofthe hardware module can be extended to be at the edges or corners of thetray (e.g. as opposed to being restricted within the circumference of acoaster 1800 for which the electrical circuitry may have been designed).

In some implementations, the tray 3200 can have bevels or edges at someplaces. In certain implementations, the tray 3200 may be flat so thatthe product 102 can be placed anywhere on the tray 3200.

FIGS. 35-37 illustrate different views of the measuring device 104formed by combining the tray of FIGS. 32-34 with coasters 1800.

Example Measuring Device—Container with Coaster(s)

FIGS. 38 and 39 illustrate different views of a container 3800 of aparticular measuring device 104 that is made operable by coupling (e.g.attaching) the container with a coaster 1800.

FIGS. 40-42 illustrate different views of the measuring device 104formed, or being formed, by combining the container 3800 with a coaster1800.

Example Adapter for Coaster

FIGS. 43-45 illustrate different views of an adapter 4300 configured tomodify a form factor of the measuring device 104. The adapter 4300 canbe a connector that allows for attaching various types of items to thecoaster 1800, such as containers, trays, or the like. Such items canform various types, shapes, and/or sizes of measuring devices 104.Connections can be made through magnetism (e.g. adapter 4300 can have aninbuilt magnet that allows magnetic coupling), taping (e.g. using doublesided tape), gluing, knitting or threading, welding, screwing, twistingand fitting two or more components until firmly attached (e.g. locked),pressing one component over another until firmly attached to each other(e.g. locked with respect to each other), and/or any other one or moreattachment mechanisms.

Example Hub and Spoke Architecture for Measuring Devices

FIG. 46 illustrates a hub and spoke architecture for multiple measuringdevices 104. The hub and spoke architecture includes a hub measuringdevice 4602 (also referred to as a hub) and multiple spoke measuringdevices 4604 (also referred to as spokes). The hub 4602 may be connectedto each spoke 4604 via a communication network 4606 that can bedifferent from the communication network 114. For example, thecommunication network 4606 can be a local area network servicing asingle location (e.g. a single building), and the communication network114 can be the internet. In some implementations, the network 4606 canbe any low-rate personal area network, operation of which may be definedby the technical standard IEEE 802.15.4. In few implementations, thecommunication any network can be a Bluetooth network. The hub 4602communicates with external systems (e.g. computing device 108) via acommunication network 114 such as the internet.

The spokes 4604 communicate directly with the hub 4602, but may notcommunicate directly with the computing device 108 and may not beconnected to the communication network 114. In some implementations, atleast some (e.g. some or all) of the spokes 4604 may communicate withone or more other spokes 4604 via the communication network 4606.

Because only the hub is in communication with external systems (e.g.computing device 108), the hub and spoke architecture is simple and easyto implement, and can reduce complexity, cost and risk. The hub andspoke architecture may allow addition of new spokes at any time,including after the hub 4602 and earlier spokes 4604 have been operable,thereby making the architecture scalable.

The spokes 4604 may include active spokes and passive spokes. The activespokes are spokes 4604 that are currently, or since recently (e.g. sincea preset amount of time ago), communicating with the hub 4602. Theinactive spokes are spokes 4604 that are currently, or since recently(e.g. since a preset amount of time ago), not communicating with the hub4602. In some implementations, the hub 4602 may constantly maintain theconnection through the communication network 4606 only with the activespokes 4604, but may establish connection with the inactive spokes 4604through the communication network 4606 only at preset intervals oftimes. Connecting with the inactive spokes 4604 through thecommunication network 4606 only at preset intervals of times canpreserve bandwidth and/or power by avoiding the need to maintain aconstant connection with the inactive spokes 4604.

Although each measuring device 104 is shown in the form of a coaster, insome implementations, any measuring device 104 in the hub and spokearchitecture may have any form (e.g. coaster, combination of tray andcoaster, combination of container and coaster, and/or the like). Incertain implementations, different measuring devices 104 may together bea part of the hub and spoke architecture.

FIG. 47 illustrates an example architecture for a measuring device 104configured to act like a spoke 4604 within the hub and spokearchitecture of FIG. 46 . The spoke 4604 can include a controller 4702,an interaction interface 4704, a location tracking radio 4706, a powermanagement system 4708, a battery 4710, a weight sensor 202, a motionsensor 204, and a near field communication (NFC) radio 4712. Thecontroller 4702 can include a radio to communicate with other measuringdevices 104, which may be connected with the spoke 4604 in a hub andspoke architecture. The controller 4702 can perform various operations.In some implementations, the functionality of the controller 4702 can beestablished and/or modified remotely by the computing device 108, whichcan be a cloud computing system.

FIG. 48 illustrates an architecture for a measuring device 104configured to act like a hub 4602 within the hub and spoke architectureof FIG. 46 . In addition to the components described above with respectto FIG. 47 , the hub 4602 can include an internet communication radio4802 that can communicate via the internet 114 to the computing device108. Although internet is described, in some implementations any othercommunication network 114 may be there and the communication radio 4802may be configured for that communication network 114.

Example Computer System

FIG. 49 is a block diagram of an example computer system 4900 (which, insome examples, can be one or more computing components within the system100, such as the measuring device 104, the communication device 106, thecomputing device 108, the client device 110, and/or any other one ormore computing components) that can be used to perform operationsdescribed above, according to some implementations described herein. Thesystem 4900 includes a processor 4910, a memory 4920, a storage device4930, and an input/output device 4940. Each of the components 4910,4920, 4930, and 4940 can be interconnected, for example, using a systembus 4950. The processor 4910 is capable of processing instructions forexecution within the system 4900. In some implementations, the processor4910 is a single-threaded processor. In another implementation, theprocessor 4910 is a multi-threaded processor. The processor 4910 iscapable of processing instructions stored in the memory 4920 or on thestorage device 4930.

The memory 4920 stores information within the system 4900. In oneimplementation, the memory 4920 is a computer-readable medium. In someimplementations, the memory 4920 is a volatile memory unit. In anotherimplementation, the memory 4920 is a non-volatile memory unit.

The storage device 4930 is capable of providing mass storage for thesystem 4900. In some implementations, the storage device 4930 is acomputer-readable medium. In various different implementations, thestorage device 4930 can include, for example, a hard disk device, anoptical disk device, a storage device that is shared over a network bymultiple computing devices (e.g., a cloud storage device), or some otherlarge capacity storage device.

The input/output device 4940 provides input/output operations for thesystem 4900. In some implementations, the input/output device 4940 caninclude one or more of a network interface devices, e.g., an Ethernetcard, a serial communication device, e.g., and RS-232 port, and/or awireless interface device, e.g., and 802.11 card. In anotherimplementation, the input/output device can include driver devicesconfigured to receive input data and send output data to externaldevices 4960, e.g., keyboard, printer and display devices. Otherimplementations, however, can also be used, such as mobile computingdevices, mobile communication devices, set-top box television clientdevices, etc.

Although an example processing system has been described in FIG. 49 ,implementations of the subject matter and the functional operationsdescribed in this specification can be implemented in other types ofdigital electronic circuitry, or in computer software, firmware, orhardware, including the structures disclosed in this specification andtheir structural equivalents, or in combinations of one or more of them.

Implementations of the subject matter and the operations described inthis specification can be implemented in digital electronic circuitry,or in computer software, firmware, or hardware, including the structuresdisclosed in this specification and their structural equivalents, or incombinations of one or more of them. Implementations of the subjectmatter described in this specification can be implemented as one or morecomputer programs, i.e., one or more modules of computer programinstructions, encoded on computer storage media (or medium) forexecution by, or to control the operation of, data processing apparatus.Alternatively, or in addition, the program instructions can be encodedon an artificially-generated propagated signal—e.g., a machine-generatedelectrical, optical, or electromagnetic signal—that is generated toencode information for transmission to suitable receiver apparatus forexecution by a data processing apparatus. A computer storage medium canbe, or be included in, a computer-readable storage device, acomputer-readable storage substrate, a random or serial access memoryarray or device, or a combination of one or more of them. Moreover,while a computer storage medium is not a propagated signal, a computerstorage medium can be a source or destination of computer programinstructions encoded in an artificially-generated propagated signal. Thecomputer storage medium can also be, or be included in, one or moreseparate physical components or media (e.g., multiple CDs, disks, orother storage devices).

The operations described in this specification can be implemented asoperations performed by a data processing apparatus on data stored onone or more computer-readable storage devices or received from othersources.

The term “data processing apparatus” encompasses all kinds of apparatus,devices, and machines for processing data, including by way of example aprogrammable processor, a computer, a system on a chip, or multipleones, or combinations, of the foregoing. The apparatus can includespecial purpose logic circuitry, e.g., an FPGA (field programmable gatearray) or an ASIC (application-specific integrated circuit). Theapparatus can also include, in addition to hardware, code that createsan execution environment for the computer program in question, e.g.,code that constitutes processor firmware, a protocol stack, a databasemanagement system, an operating system, a cross-platform runtimeenvironment, a virtual machine, or a combination of one or more of them.The apparatus and execution environment can realize various differentcomputing model infrastructures, such as web services, distributedcomputing and grid computing infrastructures.

A computer program (also known as a program, software, softwareapplication, script, or code) can be written in any form of programminglanguage, including compiled or interpreted languages, declarative orprocedural languages, and it can be deployed in any form, including as astand-alone program or as a module, component, subroutine, object, orother unit suitable for use in a computing environment. A computerprogram may, but need not, correspond to a file in a file system. Aprogram can be stored in a portion of a file that holds other programsor data (e.g., one or more scripts stored in a markup languagedocument), in a single file dedicated to the program in question, or inmultiple coordinated files (e.g., files that store one or more modules,sub-programs, or portions of code). A computer program can be deployedto be executed on one computer or on multiple computers that are locatedat one site or distributed across multiple sites and interconnected by acommunication network.

The term module, as noted herein, can include software instructions andcodes to perform a designated task or a function. A module as usedherein can be a software module or a hardware module. A software modulecan be a part of a computer program, which can include multipleindependently developed modules that can be combined or linked via alinking module. A software module can include one or more softwareroutines. A software routine is computer readable code that performs acorresponding procedure or function. A hardware module can be aself-contained component with an independent circuitry that can performvarious operations described herein.

The processes and logic flows described in this specification can beperformed by one or more programmable processors executing one or morecomputer programs to perform actions by operating on input data andgenerating output. The processes and logic flows can also be performedby, and apparatus can also be implemented as, special purpose logiccircuitry, e.g., an FPGA (field programmable gate array) or an ASIC(application-specific integrated circuit).

Processors suitable for the execution of a computer program include, byway of example, both general and special purpose microprocessors.Generally, a processor will receive instructions and data from aread-only memory or a random access memory or both. The essentialelements of a computer are a processor for performing actions inaccordance with instructions and one or more memory devices for storinginstructions and data. Generally, a computer will also include, or beoperatively coupled to receive data from or transfer data to, or both,one or more mass storage devices for storing data, e.g., magnetic,magneto-optical disks, or optical disks. However, a computer need nothave such devices. Moreover, a computer can be embedded in anotherdevice, e.g., a mobile telephone, a personal digital assistant (PDA), amobile audio or video player, a game console, a Global PositioningSystem (GPS) receiver, or a portable storage device (e.g., a universalserial bus (USB) flash drive), to name just a few. Devices suitable forstoring computer program instructions and data include all forms ofnon-volatile memory, media and memory devices, including by way ofexample semiconductor memory devices, e.g., EPROM, EEPROM, and flashmemory devices; magnetic disks, e.g., internal hard disks or removabledisks; magneto-optical disks; and CD-ROM and DVD-ROM disks. Theprocessor and the memory can be supplemented by, or incorporated in,special purpose logic circuitry.

To provide for interaction with a user, implementations of the subjectmatter described in this specification can be implemented on a computerhaving a display device, e.g., a CRT (cathode ray tube) or LCD (liquidcrystal display) monitor, for displaying information to the user and akeyboard and a pointing device, e.g., a mouse or a trackball, by whichthe user can provide input to the computer. Other kinds of devices canbe used to provide for interaction with a user as well; for example,feedback provided to the user can be any form of sensory feedback, e.g.,visual feedback, auditory feedback, or tactile feedback; and input fromthe user can be received in any form, including acoustic, speech, ortactile input. In addition, a computer can interact with a user bysending documents to and receiving documents from a device that is usedby the user; for example, by sending web pages to a web browser on auser's client device in response to requests received from the webbrowser.

Implementations of the subject matter described in this specificationcan be implemented in a computing system that includes a back-endcomponent, e.g., as a data server, or that includes a middlewarecomponent, e.g., an application server, or that includes a front-endcomponent, e.g., a client computer having a graphical user interface ora Web browser through which a user can interact with an implementationof the subject matter described in this specification, or anycombination of one or more such back-end, middleware, or front-endcomponents. The components of the system can be interconnected by anyform or medium of digital data communication, e.g., a communicationnetwork. Examples of communication networks include a local area network(“LAN”) and a wide area network (“WAN”), an inter-network (e.g., theInternet), and peer-to-peer networks (e.g., ad hoc peer-to-peernetworks).

The computing system can include clients and servers. A client andserver are generally remote from each other and typically interactthrough a communication network. The relationship of client and serverarises by virtue of computer programs running on the respectivecomputers and having a client-server relationship to each other. In someimplementations, a server transmits data (e.g., an HTML page) to aclient device (e.g., for purposes of displaying data to and receivinguser input from a user interacting with the client device). Datagenerated at the client device (e.g., a result of the user interaction)can be received from the client device at the server.

While this specification contains many specific implementation details,these should not be construed as limitations on the scope of anyinnovations or of what may be claimed, but rather as descriptions offeatures specific to particular implementations of particularinnovations. Certain features that are described in this specificationin the context of separate implementations can also be implemented incombination in a single implementation. Conversely, various featuresthat are described in the context of a single implementation can also beimplemented in multiple implementations separately or in any suitablesubcombination. Moreover, although features may be described above asacting in certain combinations and even initially claimed as such, oneor more features from a claimed combination can in some cases be excisedfrom the combination, and the claimed combination may be directed to asubcombination or variation of a subcombination.

Similarly, while operations are depicted in the drawings in a particularorder, this should not be understood as requiring that such operationsbe performed in the particular order shown or in sequential order, orthat all illustrated operations be performed, to achieve desirableresults. In certain circumstances, multitasking and parallel processingmay be advantageous. Moreover, the separation of various systemcomponents in the implementations described above should not beunderstood as requiring such separation in all implementations, and itshould be understood that the described program components and systemscan generally be integrated together in a single software product orpackaged into multiple software products.

Thus, particular implementations of the subject matter have beendescribed. Other implementations are within the scope of the claims. Insome cases, the actions recited in the claims can be performed in adifferent order and still achieve desirable results. In addition, theprocesses depicted in the accompanying figures do not necessarilyrequire the particular order shown, or sequential order, to achievedesirable results. In certain implementations, multitasking and parallelprocessing may be advantageous.

1. A method comprising: providing a measuring device attached to acontainer for holding a product, the measuring device comprising one ormore sensors configured to sense a change in the product held in thecontainer corresponding to consumption or use of the product by aconsumer; obtaining, with the measuring device, measurement data relatedto consumption or use of the product by the consumer; receiving, by acomputing device via a network, the measurement data related toconsumption or use of the product by the consumer obtained by themeasuring device; processing, by the computing device, the measurementdata related to consumption or use of the product by the consumer togenerate a notification related to the product for the consumer; andtransmitting, from the computing device via the network, thenotification to a mobile device of the consumer.
 2. The method of claim1, wherein the one or more sensors are configured to obtain measurementdata characterizing consumption or use of the product by the consumer atprogrammed intervals of time.
 3. The method of claim 1, wherein thecomputing device transmits the notification to the mobile device of theconsumer at programmed intervals of time.
 4. The method of claim 1,wherein the notification comprises a reminder to the consumer to consumeor use the product.
 5. The method of claim 4, further comprising:generating, by the mobile device of the consumer, an alarm to alert theconsumer to consume or use the product based on the reminder.
 6. Themethod of claim 1, wherein the notification notifies the consumer toreplace the product.
 7. The method of claim 1, wherein the notificationcomprises a recommendation of a replacement product to the consumer. 8.The method of claim 7, wherein the replacement product is an alternativeto the product.
 9. The method of claim 7, wherein the notification isgenerated when an amount of product remaining in the container reaches athreshold amount.
 10. The method of claim 1, wherein the productcomprises one or more medications.
 11. The method of claim 1, whereinthe one or more sensors are selected from a group consisting of: a timesensor, a weight sensor, and a motion sensor.
 12. The method of claim 1,wherein obtaining, with the measuring device, measurement datacharacterizing consumption or use of the product by the consumercomprises: obtaining, by one or more sensors of a smart devicecommunicatively coupled to the measuring device via a wirelesscommunication network, measurement data characterizing an activityperformed by the consumer; processing, by the computing device,measurement data characterizing the activity performed by the consumer;and in response to the processing, automatically activating, by thecomputing device, the measuring device to obtain measurement datacharacterizing consumption or use of the product by the consumer. 13.The method of claim 12, wherein the measurement device comprises a timesensor, and wherein the measurement data characterizing consumption oruse of the product by the consumer comprises a time at which the productis used or consumed by the consumer.
 14. The method of claim 12, furthercomprising: synchronizing measurement data characterizing the activityperformed by the consumer and the measurement data characterizingconsumption or use of the product by the consumer.
 15. The method ofclaim 12, wherein the one or more sensors of the smart device comprise acamera, and wherein the measurement data characterizing the activityperformed by the consumer comprises video data.
 16. The method of claim15, wherein processing, by the computing device, measurement datacharacterizing the activity performed by the consumer comprisesprocessing the video data using machine learning to determine anoccurrence of the activity performed by the consumer.
 17. The method ofclaim 12, wherein the one or more sensors of the smart device areselected from a group consisting of: a temperature sensor, a proximitysensor, an infrared sensor, an ultrasonic sensor, a location sensor, ahumidity sensor, a tilt sensor, a level sensor, an optics-based motionsensor, and a touch sensor.
 18. The method of claim 1, furthercomprising: storing, by a local storage module, the measurement datacharacterizing consumption or use of the product by the consumerobtained by the measuring device.
 19. The method of claim 1, furthercomprising: generating, by the computing device, a report on theconsumption or use of the product by the consumer based on themeasurement data characterizing consumption or use of the product; andtransmitting, from the computing device via the network, the report tothe mobile device of the consumer.
 20. The method of claim 1, whereinthe notification comprises an advertisement or a promotion.
 21. Themethod of claim 1, wherein the notification comprises a recommendationfor the consumer based on the measurement data related to consumption oruse of the product by the consumer.
 22. The method of claim 21, whereinthe recommendation is based on measurement data from other users thatconsume or use the product.